End-to-End (R & Python) Notebooks & Projects for Citizen Data Scientists and Machine Learning Engineers by WACAMLDS

End-to-End (R & Python) Notebooks & Projects for Citizen Data Scientists and Machine Learning Engineers

Practice makes perfect. Please practise these end-to-end notebooks (Python & R) on your computer to speed up your learning in the field of Applied Machine Learning and Data Science.

Python & R Coding are the keys towards future jobs and towards becoming Citizen
Data Scientists & Machine Learning Engineers
.

"Coding is Not Difficult - Only requires Practice"

FAQs

How to Get into Data Science — Math Or Coding?

Mathematics and coding are equally important in data science, but if you are considering to switch or start your career in the data science field; coding or programming skills are more important than deep dive to the math for various kinds of machine learning models. You should start to do more real-world projects, and able to present and answer questions clearly during the interview will definitely increase your chance to get into data science. Always remember that getting into data science is hard, but remember not to give up and continue to work hard through coding projects. (Source)

"Data Science is not all about knowing how to derive or solve mathematics equations. More importantly, it is to know how to define and solve the business problem through coding & automation." - Dr Nilimesh Halder

Is there any discount available for these Python and R programs?

Follow the link below to get 80% discount for these notebooks / programs. It comes with unlimited & unrestricted lifetime access to these notebooks. Please visit this link.

Who can use these notebooks / programs?

This product includes end-to-end Python and R programs together with enough self explained comments within each program. Anyone from Beginners to Professionals can use these, especially those who wish to build their career as Data Scientists and/or Machine Learning Engineers.

What's included?

File Icon 1700 files

Contents

Sample Notebooks
Practical_DSR_1_sklearn_DecisionTree_GridSearch_CV.html
685 KB
Practical_DSR_4_CARET_KNN_PLS_PDA_with_parameter_tuning.html
3.14 MB
100-Kickstarter-Examples.html
839 KB
Python - Applied Machine Learning & Data Science Crash Coding Course & Step-by-Step Coding Recipe
How to check installed version of Pandas.html
271 KB
How to check installed version of Matplotlib.html
269 KB
How to check installed version of NumPy.html
272 KB
How to check installed version of Python.html
271 KB
How to check installed version of scikit-learn.html
269 KB
How to check installed version of SciPy.html
269 KB
Assignment in Python.html
273 KB
Data Structure in Python.html
311 KB
Flow-Control in Python.html
314 KB
Pandas & Python Crash Course.html
317 KB
NumPy & Python Crash Course.html
300 KB
Matplotlib & Python Crash Course.html
589 KB
Random Numbers in Python.html
293 KB
Python and RDBMS.html
296 KB
How to Load Data From a csv.html
271 KB
How to Load Data From url using Pandas.html
271 KB
How to Load Data From url.html
271 KB
How to Load Data From a csv using Numpy.html
271 KB
How to Load Data From a csv using Pandas.html
272 KB
How to get class distribution in Data.html
269 KB
How to get correlation coefficient.html
270 KB
How to get data types of each feature in Data.html
269 KB
How to get dimention of Dataset.html
271 KB
How to get SKEW statistics of Dataset.html
269 KB
How to get statistics of Dataset.html
270 KB
Boxplots.html
298 KB
Correlation Matrix.html
287 KB
density plots.html
353 KB
histogram plots.html
300 KB
scatter plots.html
792 KB
How to standardize Data.html
271 KB
How to rescale Data.html
271 KB
binarization.html
271 KB
normalization.html
271 KB
Feature Extraction with RFE.html
273 KB
How to get Feature Importance.html
271 KB
Feature Extraction with Univariate Statistics.html
272 KB
How to get important Feature with PCA.html
271 KB
Cross Validation.html
271 KB
How to prepare train test dataset.html
271 KB
Leave One Out Cross Validation.html
271 KB
Shuffle Split Cross Validation.html
272 KB
How to get Classification Accuracy.html
271 KB
How to get Classification AUC ROC.html
271 KB
How to get Classification Confusion Matrix.html
272 KB
How to get Classification LogLoss Metric.html
271 KB
How to get Classification Report.html
272 KB
How to get Regression MAE.html
272 KB
How to get Regression MSE.html
272 KB
How to get Regression R_squared.html
272 KB
CART Algorithm.html
271 KB
KNN Algorithm.html
271 KB
LDA Algorithm.html
271 KB
LR Algorithm.html
271 KB
Naive Bayes Algorithm.html
271 KB
SVM Algorithm.html
271 KB
ElasticNet Algorithm.html
271 KB
CART Algorithm.html
271 KB
KNN Algorithm.html
271 KB
Lasso Algorithm.html
271 KB
Linear Regression Algorithm.html
271 KB
Ridge Algorithm.html
271 KB
SVM Algorithm.html
271 KB
Compare Algorithms with diabetes dataset.html
290 KB
Compare Algorithms with iris dataset.html
780 KB
How to create a pipeline that extracts features from the data and create model.html
273 KB
How to create a pipeline that standardizes the data and create model.html
272 KB
pima-indians-diabetes.data.csv
22.7 KB
AdaBoost Ensembles.html
285 KB
Bagging CART Ensembles.html
284 KB
Extra Trees Ensembles.html
282 KB
Gradient Boosting Ensembles.html
286 KB
pima-indians-diabetes.data.csv
22.7 KB
Voting Ensembles Ensembles.html
287 KB
Random Forest Ensembles.html
283 KB
Random Search Cross Validation.html
271 KB
Grid Search Cross Validation.html
272 KB
how to save and load model with joblib.html
272 KB
how to save and load model with pickle.html
272 KB
iris.data.csv
4.44 KB
MultiClass Classification.html
378 KB
sonar.all-data.csv
85.7 KB
Binary Classification.html
1.51 MB
housing.csv
47.9 KB
Regression.html
574 KB
Python Machine Learning Crash Course - Learn By Coding.zip
10.6 MB
R - Applied Machine Learning & Data Science Crash Coding Course and Step-by-Step Coding Recipe
How to load data from a R-dataset library.html
277 KB
How to load data from a csv file.html
269 KB
How to load data from a R library.html
272 KB
How to load data from a url.html
271 KB
How to load data from mlbench library.html
295 KB
How to display head and tail of a dataset in R.html
293 KB
How to determine pearson spearman correlation in R.html
272 KB
How to get mean and standard deviation in R.html
272 KB
How to get summary statistics in R.html
273 KB
How to know datatypes in R.html
271 KB
How to know dimention of a dataset in R.html
272 KB
How to summarize calss distribution in R.html
270 KB
How to summarize correlation coefficients in R.html
273 KB
BOX plot in R.html
422 KB
BAR plot in R.html
471 KB
DENSITY plot in R.html
476 KB
Display Missing Data in R.html
438 KB
Histogram plot in R.html
397 KB
BOX plot in R.html
335 KB
Density plot in R.html
440 KB
Correlation plot in R.html
387 KB
Scatter Matrix plot in R.html
736 KB
Fix imbalance Dataset in R.html
269 KB
mark missing values in R.html
286 KB
impute missing values in R.html
295 KB
remove duplicate values in R.html
269 KB
remove outliers in R.html
286 KB
remove NULL values in R.html
268 KB
remove highly correlated features in R.html
287 KB
recursive feature elimination in R.html
338 KB
feature ranking with importance in R.html
381 KB
center transformation in R.html
270 KB
ica transformation in R.html
271 KB
boxcox transformation in R.html
270 KB
normalize transformation in R.html
275 KB
pca transformation in R.html
270 KB
scale in R.html
270 KB
standardize in R.html
270 KB
ordinary least squares regression in R.html
269 KB
principal component regression in R.html
269 KB
partial least squares regression in R.html
269 KB
stepwise linear regression in R.html
271 KB
ridge regression in R.html
269 KB
lasso regression in R.html
270 KB
elastic net regression in R.html
269 KB
conditional regression trees in R.html
270 KB
feed forward neural networks in R.html
271 KB
cubist algorithm in R.html
269 KB
gradient boosted machine in R.html
269 KB
KNN in R.html
269 KB
multivariate adaptive regression in R.html
270 KB
random forest algorithm in R.html
269 KB
regression with bagging_CART in R.html
269 KB
regression with classification and regression trees in R.html
269 KB
support vector machine in R.html
269 KB
bagging CART in R.html
269 KB
classification and regression tree in R.html
269 KB
C5.0 in R.html
269 KB
gradient boosted machine in R.html
270 KB
feed forward neural network in R.html
271 KB
KNN in R.html
269 KB
linear discriminant analysis in R.html
269 KB
logistic regression for binaryclass classification in R.html
270 KB
logistic regression for multiclass classification in R.html
277 KB
partial least squares discriminant in R.html
269 KB
naive bayes in R.html
269 KB
random forest in R.html
269 KB
SVM in R.html
269 KB
Algorithm Checkpoint with CARET in R.html
319 KB
Binary Classification with CARET in R.html
316 KB
Regression with CARET in R.html
285 KB
kfold cross validation in R.html
269 KB
bootstrap in R.html
270 KB
dataset split in R.html
271 KB
leave one out cross validation in R.html
269 KB
repeated kfold cross validation in R.html
270 KB
kappa metric in R.html
269 KB
logloss metric in R.html
269 KB
accuracy metric in R.html
269 KB
rmse metric in R.html
269 KB
roc metric in R.html
269 KB
rsquared metric in R.html
269 KB
model selection in R using dotplot.html
326 KB
model selection in R using boxplot.html
331 KB
model selection in R using densityplot.html
434 KB
model selection in R using parallelplot.html
578 KB
model selection in R using scatterplot matrix.html
587 KB
model selection in R using summary results.html
273 KB
model selection in R using xyplot.html
330 KB
statistical significance of difference between model predictions.html
357 KB
manual grid search in R.html
382 KB
automatic grid search in R.html
418 KB
custom grid search in R.html
434 KB
optimal parameter search in R.html
270 KB
random search in R.html
342 KB
blending in R.html
270 KB
bagging in R.html
269 KB
stacking in R.html
325 KB
save in R.html
272 KB
crash course in R.html
282 KB
Diabetes Prediction in R.html
424 KB
Ionosphere Prediction in R.html
993 KB
Sonar Prediction in R.html
893 KB
Breast Cancer Prediction in R.html
1.69 MB
crash course in R.html
282 KB
IRIS Prediction in R.html
385 KB
Glass Prediction in R.html
1.41 MB
crash course in R.html
282 KB
Abalone Prediction in R.html
956 KB
Boston House Price Prediction in R.html
926 KB
R Machine Learning & Data Science Crash Course - Learn By Coding.zip
25.5 MB
Programming Problem-Solution in Data Science 001 - Let's start coding with R: Data Science preliminaries and Statistics
Notebook 001 - Linear Regression in R using OLS Regression.html
313 KB
Notebook 002 - Linear Regression in R using Stepwise Regression.html
316 KB
Notebook 003 - Linear Regression in R using Principal Component Regression.html
313 KB
Notebook 004 - Linear Regression in R using Partial Least Squared Regression.html
313 KB
Notebook 005 - Variables and Data Frames in R.html
275 KB
Notebook 006 - How to work with Control Flow in R.html
270 KB
Notebook 007 - How to utilize ggplot to visualise histograms in R.html
513 KB
Notebook 008 - How to analyse a Dataset in R.html
377 KB
Notebook 009 - How to visualise Dataset in R.html
735 KB
Notebook 010 - How to visualise correlation plot in R.html
976 KB
Notebook 011 - How to visualise a Dataset according to its Class variables in R.html
967 KB
Notebook 012 - How to split train test dataset for machine learning in R.html
270 KB
Notebook 013 - How to setup cross validation and control parameters for machine learning in R.html
271 KB
Notebook 014 - How to setup a Machine Learning Classification problem in R.html
369 KB
Notebook 015 - How to setup a Machine Learning Regression problem in R.html
406 KB
Notebook 016 - Automatic tuning of Random Forest Parameters.html
533 KB
Notebook 017 - How to use stacking of Machine Learning Algorithms in R.html
391 KB
Notebook 018 - Manual parameter tuning of Neural Networks.html
436 KB
Notebook 019 - How to transpose a matrix in R.html
271 KB
Notebook 020 - How to create histogram plots in R.html
407 KB
Notebook 021 - How to add a normal curve to a Histogram plot in R.html
364 KB
Notebook 022 - How to create Density plot in R.html
478 KB
Notebook 023 - How to create dot plot in R.html
457 KB
Notebook 024 - How to create bar chart in R.html
448 KB
Notebook 025 - How to create pie chart in R.html
577 KB
Notebook 026 - How to create box chart in R.html
552 KB
Notebook 027 - How to create scatter chart in R.html
723 KB
Notebook 028 - How to create 3D scatter chart in R.html
477 KB
Notebook 029 - How to find correlations among feature variables in R.html
279 KB
Notebook 030 - How to visualise correlations among feature variables in R.html
926 KB
Notebook 031 - How to utilise caret Linear regression model in R.html
272 KB
Notebook 032 - How to utilise caret Logistic regression model in R.html
272 KB
Notebook 033 - How to utilise caret LDA in R.html
272 KB
Notebook 034 - How to utilise caret Regularised Regression model in R.html
282 KB
Notebook 035 - How to utilise caret KNN model in R.html
282 KB
Notebook 036 - How to utilise caret Naive Bayes model in R.html
271 KB
Notebook 037 - How to utilise caret SVM model in R.html
289 KB
Notebook 038 - How to utilise classification and regression tree model in R.html
345 KB
Notebook 039 - How to utilise XGBoost - xgbLinear model in R.html
551 KB
Notebook 040 - How to utilise XGBoost - xgbTree model in R.html
1.08 MB
Notebook 041 - How to preprocess data in R using scale method.html
271 KB
Notebook 042 - How to preprocess data in R using center method.html
271 KB
Notebook 043 - How to preprocess data in R using scale & center method.html
271 KB
Notebook 044 - How to preprocess data in R using normalisation.html
271 KB
Notebook 045 - How to preprocess data in R using Box-Cox Transformation.html
271 KB
Notebook 046 - How to do PCA in R to preprocess data.html
271 KB
Notebook 047 - How to do ICA in R to preprocess data.html
272 KB
Notebook 048 - How to utilise Confusion Matrix in R.html
352 KB
Notebook 049 - How to save trained model in R.html
380 KB
Notebook 050 - How to compare performance of different trained models in R.html
1.35 MB
Notebook 051 - How to utilize ggplot to visualise Data (scatter plots) in R.html
779 KB
Notebook 052 - How to visualise Data in multiple groups in R.html
877 KB
Notebook 053 - How to visualise Data in gray scale in R.html
429 KB
Notebook 054 - How to visualise Data in 2D density graph in R.html
1.64 MB
Notebook 055 - How to visualise scatter plots with ellipses in R.html
741 KB
Notebook 056 - How to visualise scatter plots with rectangular bins in R.html
399 KB
Notebook 057 - How to visualise scatter plots with marginal density plots in R.html
885 KB
Notebook 058 - How to utilise (load & view) built-in datasets in R.html
306 KB
Notebook 059 - How to generate histograms in R using ggpubr package.html
668 KB
Notebook 060 - How to generate Boxplots in R using ggpubr package.html
743 KB
Notebook 061 - How to generate Violin plots in R using ggpubr package.html
896 KB
Notebook 062 - How to generate Violin plots with box plots in R using ggpubr package.html
687 KB
Notebook 063 - How to generate Bar plots in R using ggpubr package.html
632 KB
Notebook 064 - How to generate deviation plots in R using ggpubr package.html
469 KB
Notebook 065 - How to generate dot charts in R using ggpubr package.html
642 KB
Notebook 066 - How to plot p-values in R using ggpubr package.html
547 KB
Notebook 067 - How to plot Mean and Std in R using ggpubr package.html
354 KB
Notebook 068 - How to plot p-values in R.html
426 KB
Notebook 069 - How to do line and bar plot with mean and std in R.html
576 KB
Notebook 070 - How to perform Descriptive Statistics in R.html
281 KB
Notebook 071 - How to plot Descriptive Statistics in R.html
690 KB
Notebook 072 - Regression Analysis in R - How to use predict function.html
276 KB
Notebook 073 - Regression Analysis in R - How to visualise.html
386 KB
Notebook 074 - Correlation Analysis in R - How to analyse and visualise correlated Data.html
362 KB
Notebook 075 - Correlation Matrix in R - How to visualise.html
1.28 MB
Notebook 076 - How to analyse and visualise One-Sample-T-Test in R.html
411 KB
Notebook 077 - How to analyse and visualise One-Sample-Wilcoxon-Test in R.html
413 KB
Notebook 078 - How to analyse and visualise Two-Samples-T-Test in R.html
318 KB
Notebook 079 - How to analyse and visualise Two-Samples-Wilcoxon-Test in R.html
318 KB
Notebook 080 - How to analyse and visualise Two-Samples-T-Test (Paired) in R.html
318 KB
Notebook 081 - How to visualise optimal number of Clusters in R.html
570 KB
Notebook 082 - How to visualise Clusters in R.html
3.05 MB
Notebook 083 - How to compute CLARA (Clustering Large Applications) in R.html
482 KB
Notebook 084 - How to visualise Hierarchical Clustering (agglomerative) in R.html
707 KB
Notebook 085 - How to visualise Hierarchical Clustering in R using (cluster) pkg.html
442 KB
Notebook 086 - How to compare Dendrograms in R.html
755 KB
Notebook 087 - How to Create multiple dendrograms by chaining in R.html
1.45 MB
Notebook 088 - How to visualise Dendrograms (Hierarchical Clustering) in R.html
2.15 MB
Notebook 089 - How to visualise a heatmap in R using heatmap().html
605 KB
Notebook 090 - How to visualise interactive heatmap in R using d3heatmap().html
863 KB
Notebook 091 - How to use ComplexHeatmap package to generate heatmaps in R.html
1010 KB
End-to-End Learn by Coding Examples - Introduction to Data Science with R.zip
59.7 MB
Programming Problem-Solution in Data Science 002 - Linear Algebra, Data Analytics & Data Preprocessing in Python: Examples using Pandas
Notebook 001 - How to Create a Vector or Matrix in Python.html
271 KB
Notebook 002 - How to create a sparse Matrix in Python.html
272 KB
Notebook 003 - How to select elecments from Numpy array in Python.html
272 KB
Notebook 004 - How to reshape a Numpy array in Python.html
270 KB
Notebook 005 - How to convert a dictionary to a matrix or nArray in Python.html
271 KB
Notebook 006 - How to invert a matrix or nArray in Python.html
270 KB
Notebook 007 - How to Calculate Trace of a Matrix.html
270 KB
Notebook 008 - How to calculate Diagonal of a Matrix.html
270 KB
Notebook 009 - How to Calculate Determinant of a Matrix or ndArray.html
271 KB
Notebook 010 - How to Flatten a Matrix.html
271 KB
Notebook 011 - How to Calculate Mean, Variance and Std a Matrix or ndArray.html
271 KB
Notebook 012 - How to find the Rank of a Matrix.html
270 KB
Notebook 013 - How to find Maximum and Minimum values in a Matrix.html
271 KB
Notebook 014 - How to calculate dot product of two vectors.html
276 KB
Notebook 015 - How to ADD numerical value to each electment of a matrix.html
270 KB
Notebook 016 - How to SUBTRACT numerical value to each electment of a matrix.html
270 KB
Notebook 017 - How to MULTIPLY numerical value to each electment of a matrix.html
270 KB
Notebook 018 - How to Divide each electment of a matrix by a numerical value.html
270 KB
Notebook 019 - How to add and subtract between matrices.html
271 KB
Notebook 020 - How to load features from a Dictionary in python.html
272 KB
Notebook 021 - How to load sklearn Boston Housing data.html
269 KB
Notebook 022 - How to Create simulated data for regression in Python.html
272 KB
Notebook 023 - How to Create simulated data for classification in Python.html
273 KB
Notebook 024 - How to Create simulated data for clustering in Python.html
272 KB
Notebook 025 - How to prepare a machine leaning workflow in Python.html
275 KB
Notebook 026 - How to convert Categorical features to Numerical Features in Python.html
273 KB
Notebook 027 - How to impute missing class labels in Python.html
271 KB
Notebook 028 - How to impute missing class labels using nearest neighbours in Python.html
274 KB
Notebook 029 - How to delete instances with missing values in Python.html
270 KB
Notebook 030 - How to find outliers in Python.html
283 KB
Notebook 031 - How to encode ordinal categorical features in Python.html
271 KB
Notebook 032 - How to deal with imbalance classes with downsampling in Python.html
274 KB
Notebook 033 - How to deal with imbalance classes with upsampling in Python.html
274 KB
Notebook 034 - How to deal with outliers in Python.html
273 KB
Notebook 035 - How to impute missing values with means in Python.html
273 KB
Notebook 036 - One hot Encoding with multiple labels in Python.html
271 KB
Notebook 038 - How to process categorical features in Python.html
274 KB
Notebook 037 - One hot Encoding with nominal categorical features in Python.html
271 KB
Notebook 039 - How to rescale features in Python.html
270 KB
Notebook 040 - How to standardise features in Python.html
270 KB
Notebook 041 - How to standarise IRIS Data in Python.html
272 KB
Notebook 042 - How to split DateTime Data to create multiple feature in Python.html
272 KB
Notebook 043 - How to claculate difference between Dates in Python.html
271 KB
Notebook 044 - How to encode Days of a week in Python.html
270 KB
Notebook 045 - How to deal with missing values in a Timeseries in Python.html
274 KB
Notebook 047 - How to deal with Rolling Tine Window in Python.html
272 KB
Notebook 046 - How to introduce LAG time in Python.html
272 KB
Notebook 048 - How to select DateTime within a range in Python.html
270 KB
Notebook 049 - How to convert Strings to DateTimes in Python.html
270 KB
Notebook 050 - How to deal with an Item in a List in Python.html
271 KB
End-to-End Learn by Coding Examples 001-050 - Data Analytics & Preprocessing in Python.zip
2.55 MB
Programming Problem-Solution in Data Science 003: Data Analytics & Data Frame in Python: Examples using Pandas
Notebook 051 - How to do numerical operations in Python using Numpy.html
270 KB
Notebook 052 - How to use CONTINUE and BREAK statement within a loop in Python.html
271 KB
Notebook 053 - How to convert STRING to DateTime in Python.html
275 KB
Notebook 054 - How to Create and Delete a file in Python.html
270 KB
Notebook 055 - How to deal with Date & Time Basics in Python.html
272 KB
Notebook 056 - How to deal with Dictionary Basics in Python.html
272 KB
Notebook 057 - How to find MIN, MAX in a Dictionary.html
270 KB
Notebook 058 - How to define FOR Loop in Python.html
269 KB
Notebook 059 - How to define WHILE Loop in Python.html
270 KB
Notebook 060 - How to create RANDOM Numbers in Python.html
271 KB
Notebook 061 - How to index and slice Numpy arrays in Python.html
275 KB
Notebook 062 - How to iterate a list using if-else in Python.html
270 KB
Notebook 063 - How to iterate over multiple lists in Python.html
270 KB
Notebook 064 - How to use lambda function in Python.html
270 KB
Notebook 065 - How to do common mathematical operations in Python.html
274 KB
Notebook 066 - How to use nested loops in Python.html
273 KB
Notebook 067 - How to choose a random elecment from a list in Python.html
269 KB
Notebook 068 - How to use if and if-else in Python.html
271 KB
Notebook 069 - How to apply functions in a Group in a Pandas DataFrame.html
276 KB
Notebook 070 - How to do Data Analysis in a Pandas DataFrame.html
286 KB
Notebook 071 - How to assign a new column in a Pandas DataFrame.html
270 KB
Notebook 072 - How to apply arithmatic operations on a Pandas DataFrame.html
276 KB
Notebook 073 - How to divide a list into chunks in python.html
271 KB
Notebook 074 - How to preprocess string data within a Pandas DataFrame.html
276 KB
Notebook 075 - How to create a dictionary from multiple lists.html
270 KB
Notebook 076 - How to convert categorical variables into numerical variables in Python.html
273 KB
Notebook 077 - How to convert string categorical variables into numerical variables in Python.html
273 KB
Notebook 078 - How to convert string categorical variables into numerical variables using Label Encoder.html
274 KB
Notebook 079 - How to convert string variables into DateTime variables in Python.html
271 KB
Notebook 080 - How to insert a new column based on condition in Python.html
275 KB
Notebook 081 - How to create a new column based on a condition in Python.html
274 KB
Notebook 082 - How to create lists from Dictionary in Python.html
271 KB
Notebook 083 - How to create crosstabs from a Dictionary in Python.html
279 KB
Notebook 084 - How to delete duplicates from a Pandas DataFrame.html
274 KB
Notebook 085 - How to get descriptive statistics of a Pandas DataFrame.html
277 KB
Notebook 086 - How to drop ROW and COLUMN in a Pandas DataFrame.html
275 KB
Notebook 087 - How to filter in a Pandas DataFrame.html
274 KB
Notebook 088 - How to find the largest value in a Pandas DataFrame.html
273 KB
Notebook 089 - How to group rows in a Pandas DataFrame.html
276 KB
Notebook 090 - How to present Hierarchical Data in Pandas.html
282 KB
Notebook 091 - How to JOIN and MERGE Pandas DataFrame.html
286 KB
Notebook 092 - How to list unique values in a Pandas DataFrame.html
272 KB
Notebook 093 - How to map values in a Pandas DataFrame.html
274 KB
Notebook 094 - How to deal with missing values in a Pandas DataFrame.html
282 KB
Notebook 096 - How to Normalise a Pandas DataFrame Column.html
272 KB
Notebook 097 - How to create Pivot table using a Pandas DataFrame.html
276 KB
Notebook 095 - How to calculate MOVING AVG in a Pandas DataFrame.html
276 KB
Notebook 098 - How to format string in a Pandas DataFrame Column.html
272 KB
Notebook 099 - How to randomly sample a Pandas DataFrame.html
274 KB
Notebook 100 - How to rank a Pandas DataFrame.html
273 KB
End-to-End Learn by Coding Examples 051-100 - Data Analytics, DataFrame & Pandas in Python.zip
2.55 MB
Programming Problem-Solution in Data Science 004: Data Analysis, Data Visualisation and Machine Learning using Python: Examples with Popular Python Packages
Notebook 101 - How to reindex Pandas Series and DataFrames.html
275 KB
Notebook 102 - How to rename column header of a Pandas DataFrame.html
273 KB
Notebook 103 - How to rename multiple column headers in a Pandas DataFrame.html
273 KB
Notebook 104 - How to replace multiple values in a Pandas DataFrame.html
274 KB
Notebook 105 - How to save Pandas DataFrame as CSV file.html
273 KB
Notebook 106 - How to search a value within a Pandas DataFrame column.html
272 KB
Notebook 107 - How to search a value within a Pandas DataFrame row.html
270 KB
Notebook 108 - How to select rows with multiple filters.html
271 KB
Notebook 109 - How to sort rows within a Pandas DataFrame.html
273 KB
Notebook 110 - How to do string munging in Pandas.html
275 KB
Notebook 111 - How to use seaborn to visualise a Pandas dataframe.html
408 KB
Notebook 112 - How to utilise Pandas dataframe & series for data wrangling.html
278 KB
Notebook 113 - How to generate BAR plot using pandas DataFrame.html
290 KB
Notebook 114 - How to utilise timeseries in pandas.html
296 KB
Notebook 115 - How to generate timeseries using Pandas and Seaborn.html
304 KB
Notebook 116 - How to generate scatter plot using Pandas and Seaborn.html
332 KB
Notebook 117 - How to generate grouped BAR plot in Python.html
293 KB
Notebook 118 - How to generate PIE plot in Python.html
292 KB
Notebook 119 - How to generate stacked BAR plot in Python.html
290 KB
Notebook 120 - How to determine Pearson's correlation in Python.html
293 KB
Notebook 121 - How to determine Spearman's correlation in Python.html
288 KB
Notebook 122 - How to reduce dimentionality on Sparse Matrix in Python.html
275 KB
Notebook 123 - How to reduce dimentionality using PCA in Python.html
274 KB
Notebook 124 - How to extract features using PCA in Python.html
273 KB
Notebook 125 - How to select features using best ANOVA F-values in Python.html
276 KB
Notebook 126 - How to select features using chi-squared in Python.html
276 KB
Notebook 127 - How to drop out highly correlated features in Python.html
279 KB
Notebook 128 - How to do recursive feature elimination in Python.html
272 KB
Notebook 129 - How to do recursive feature elimination in Python (DecisionTreeRegressor).html
276 KB
Notebook 130 - How to do variance thresholding in Python for feature selection.html
271 KB
Notebook 131 - How to split train test data using sklearn and python.html
271 KB
Notebook 132 - How to check model's accuracy using cross validation in Python.html
272 KB
Notebook 133 - How to check model's f1-score using cross validation in Python.html
272 KB
Notebook 134 - How to check model's precision score using cross validation in Python.html
272 KB
Notebook 135 - How to check model's recall score using cross validation in Python.html
272 KB
Notebook 136 - How to check model's AUC score using cross validation in Python.html
272 KB
Notebook 137 - How to check model's Average precision score using cross validation in Python.html
273 KB
Notebook 138 - How to generate classification report and confusion matrix in Python.html
272 KB
Notebook 139 - How to plot a learning Curve in Python.html
330 KB
Notebook 140 - How to plot a ROC Curve in Python.html
340 KB
Notebook 141 - How to plot Validation Curve in Python.html
319 KB
Notebook 142 - How to tune Hyper-parameters using Grid Search in Python.html
272 KB
Notebook 143 - How to tune Hyper-parameters using Random Search in Python.html
273 KB
Notebook 144 - How to select model using Grid Search in Python.html
274 KB
Notebook 145 - How to optimize hyper-parameters of a Logistic Regression model using Grid Search in Python.html
277 KB
Notebook 146 - How to optimize hyper-parameters of a DecisionTree model using Grid Search in Python.html
277 KB
Notebook 147 - How to create and optimize a baseline linear regression model.html
276 KB
Notebook 148 - How to create and optimize a baseline Ridge Regression model.html
276 KB
Notebook 149 - How to create and optimize a baseline Lasso Regression model.html
276 KB
Notebook 150 - How to create and optimize a baseline ElasticNet Regression model.html
276 KB
End-to-End Learn by Coding Examples 101-150 - Data Analysis, Data Visualisation & Machine Learning in Python.zip
3.44 MB
Programming Problem-Solution in Data Science 005 - Kickstarter Examples: Classification, Regression & Clustering using Python
Notebook 151 - How to create and optimize a baseline Decision Tree model for Regression.html
278 KB
Notebook 153 - How to create and optimize a baseline Decision Tree model for MultiClass Classification.html
278 KB
Notebook 154 - How to use nearest neighbours for Regression.html
277 KB
Notebook 152 - How to create and optimize a baseline Decision Tree model for Binary Classification.html
279 KB
Notebook 155 - How to use nearest neighbours for Classification.html
279 KB
Notebook 156 - How to do Agglomerative Clustering in Python.html
316 KB
Notebook 158 - How to do Affinity based Clustering in Python.html
329 KB
Notebook 157 - How to do KMeans Clustering in Python.html
328 KB
Notebook 159 - How to do DBSCAN based Clustering in Python.html
328 KB
Notebook 160 - How to do MinShift Clustering in Python.html
326 KB
Notebook 161 - How to use Classification and Regression Tree in Python.html
277 KB
Notebook 162 - How to use Adaboost Classifier and Regressor in Python.html
277 KB
Notebook 164 - How to use GradientBoosting Classifier and Regressor in Python.html
324 KB
Notebook 163 - How to use RandomForest Classifier and Regressor in Python.html
321 KB
Notebook 165 - How to use MLP Classifier and Regressor in Python.html
324 KB
Notebook 166 - How to connect MySQL DB in Python.html
272 KB
Notebook 168 - How to use CatBoost Classifier and Regressor in Python.html
425 KB
Notebook 169 - How to use LightGBM Classifier and Regressor in Python.html
324 KB
Notebook 167 - How to use XgBoost Classifier and Regressor in Python.html
324 KB
Notebook 171 - How to import a CSV file in Python.html
272 KB
Notebook 170 - How to use SVM Classifier and Regressor in Python.html
305 KB
Notebook 174 - How to classify "wine" using sklearn nearest neighbors model - Multiclass Classification.html
273 KB
Notebook 173 - How to classify "wine" using sklearn Naive Bayes mdeol - Multiclass Classification.html
278 KB
Notebook 172 - How to classify "wine" using sklearn linear_models - Multiclass Classification.html
279 KB
Notebook 175 - How to classify "wine" using sklearn LDA and QDA model - Multiclass Classification.html
279 KB
Notebook 177 - How to classify "wine" using sklearn ensemble (Bagging) model - Multiclass Classification.html
279 KB
Notebook 176 - How to classify "wine" using sklearn tree model - Multiclass Classification.html
276 KB
Notebook 179 - How to classify "wine" using different Boosting models - Multiclass Classification.html
330 KB
Notebook 178 - How to classify "wine" using sklearn ensemble (Boosting) model - Multiclass Classification.html
277 KB
Notebook 180 - How to visualise a tree model - Multiclass Classification.html
429 KB
Notebook 182 - How to use Regression Metrics in Python.html
275 KB
Notebook 181 - How to use Classification Metrics in Python.html
277 KB
Notebook 184 - How to implement voting ensemble in Python.html
273 KB
Notebook 185 - How to save trained model in Python.html
273 KB
Notebook 183 - How to compare sklearn classification algorithms in Python.html
295 KB
Notebook 186 - How to visualise XGBoost tree in Python.html
273 KB
Notebook 188 - How to evaluate XGBoost model with learning curves.html
311 KB
Notebook 187 - How to visualise XGBoost feature importance in Python.html
303 KB
Notebook 189 - How to evaluate XGBoost model with learning curves.html
380 KB
Notebook 190 - How to parallalise execution of XGBoost and cross validation in Python.html
275 KB
Notebook 191 - How to optimise number of trees in XGBoost.html
276 KB
Notebook 192 - How to optimise size (depth) of trees in XGBoost.html
277 KB
Notebook 193 - How to optimise learning rates in XGBoost.html
276 KB
Notebook 194 - How to optimise learning rates in XGBoost.html
279 KB
Notebook 195 - How to find optimal parameters using GridSearchCV.html
276 KB
Notebook 197 - How to find optimal parameters using GridSearchCV for Regression.html
276 KB
Notebook 196 - How to find optimal parameters using RandomizedSearchCV.html
276 KB
Notebook 198 - How to find optimal parameters using RandomizedSearchCV for Regression.html
276 KB
Notebook 200 - How to find optimal parameters for CatBoost using GridSearchCV for Classification.html
278 KB
Notebook 199 - How to find optimal parameters for CatBoost using GridSearchCV for Regression.html
276 KB
End-to-End Learn by Coding Examples 151-200 - Classification-Clustering-Regression in Python.zip
5.19 MB
Programming Problem-Solution in Data Science 006 - Time Series Forecasting using Python: BJ-Sales Dataset
BJsales_in_R.csv
2.62 KB
TSF_1_ARMA_model.html
542 KB
TSF_2_ARIMA_model.html
606 KB
TSF_3_SARIMA_model.html
668 KB
TSF_4_LSTM_model.html
627 KB
TSF_5_CNN_model.html
628 KB
TSF_6_MLP_model.html
511 KB
TSF_Seasonal_RandomTrend_model.html
637 KB
TSF_Seasonal_RandomWalk_model.html
653 KB
TSF_Seasonal_General_ARIMA_model.html
766 KB
Python.zip
5.3 MB
Programming Problem-Solution in Data Science 007 - Time Series Forecasting using R: BJ-Sales Dataset
BJsales_in_R.csv
2.62 KB
TSF_1_LR_model.html
277 KB
TSF_2_LR_model.html
277 KB
TSF_Poly_models.html
329 KB
TSF_log_model.html
277 KB
TSF_HoltWinters_model.html
274 KB
TSF_ARIMA_models.html
364 KB
TSF_NeuralNetwork_models.html
275 KB
R.zip
1.69 MB
Programming Problem-Solution in Data Science 008 - Multi-class Classification using Python and Ames Housing Dataset
AmesHousing.csv
936 KB
Notebook-01.html
990 KB
Notebook-02.html
884 KB
Notebook-03.html
882 KB
Notebook-04.html
1000 KB
Notebook-05.html
995 KB
Notebook-06.html
878 KB
Notebook-07.html
844 KB
Notebook-08.html
865 KB
Python.zip
87.6 MB
Programming Problem-Solution in Data Science 009 - Regression in Python | Boston Housing Dataset | Applied Data Science & Machine Learning
BostonHousing.csv
34.9 KB
DSR_1_sklearn_DT_GridSearch_and_RandomSearch_CV.html
1.86 MB
DSR_2_sklearn_RandomForest_GridSearch_and_RandomSearch_CV.html
1.85 MB
DSR_3_sklearn_GradientBoosting_GridSearch_and_RandomSearch_CV.html
1.85 MB
DSR_4_sklearn_XGBoost_GridSearch_and_RandomSearch_CV.html
1.85 MB
DSR_5_sklearn_LightGBM_GridSearch_and_RandomSearch_CV.html
1.83 MB
DSR_6_sklearn_Kears_TensorFlow.html
1.92 MB
DSR_7_sklearn_MLP_GridSearch_and_RandomSearch_CV.html
1.82 MB
Python.zip
18 MB
Programming Problem-Solution Codes 010 - Regression in R | Boston Housing Dataset | Applied Machine Learning & Data Science
housing.csv
47.9 KB
DSR_1_CARET_Xgboost_with_parameter_tuning.html
4.86 MB
DSR_2_CARET_Bagging_RandomForest_with_parameter_tuning.html
3.27 MB
DSR_3_CARET_NeuralNetworks_with_parameter_tuning.html
5.02 MB
DSR_4_Keras_Tensorflow.html
3.24 MB
DSR_5_Keras_Tensorflow-Version-2.html
3.11 MB
R.zip
27.3 MB
Programming Problem-Solution in Data Science 011 - Classification in Python | IRIS Dataset | Use of Different Machine Learning Algorithms with Cross Validation
iris.data.csv
4.44 KB
Practical_DSR_1_sklearn_DecisionTree_GridSearch_CV.html
685 KB
Practical_DSR_2_sklearn_DecisionTree_MonteCarlo_CV-.html
696 KB
Practical_DSR_3_sklearn_RandomForest_GridSearch_CV.html
669 KB
Practical_DSR_4_sklearn_RandomForest_MonteCarlo_CV.html
686 KB
Practical_DSR_5_sklearn_GradientBoosting_GridSearch_CV.html
695 KB
Practical_DSR_6_sklearn_GradientBoosting_MonteCarlo_CV.html
648 KB
Practical_DSR_7_sklearn_XGBoost_GridSearch_CV.html
635 KB
Practical_DSR_8_sklearn_XGBoost_MonteCarlo_CV.html
652 KB
Practical_DSR_13_keras_tensorflow.html
697 KB
Practical_DSR_14_using-H2O.html
617 KB
Practical_DSR_15_using-TURICREATE.html
449 KB
Python.zip
7.04 MB
Programming Problem-Solution in Data Science 012 - Classification in R | IRIS Dataset | Use of Different Machine Learning Algorithms with Cross Validation
iris.data.csv
4.51 KB
Practical_DSR_1_CARET_LDA_with_parameter_tuning.html
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Practical_DSR_2_CARET_QDA_with_parameter_tuning.html
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Practical_DSR_3_CARET_SVM_with_parameter_tuning.html
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Practical_DSR_4_CARET_KNN_PLS_PDA_with_parameter_tuning.html
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Practical_DSR_5_CARET_Naive_Bayes_with_parameter_tuning.html
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Practical_DSR_6_CARET_Bagging_with_parameter_tuning.html
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Practical_DSR_7_CARET_RandomForest_with_parameter_tuning.html
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Practical_DSR_8_CARET_XGBoost_with_parameter_tuning.html
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Practical_DSR_9_CARET_NeuralNetwork_with_parameter_tuning.html
2.82 MB
Practical_DSR_10_CARET_Keras_TensorFlow_with_parameter_tuning.html
2.92 MB
Practical_DSR_11_CARET_H2O.html
2.74 MB
R.zip
42.7 MB
Programming Problem-Solution in Data Science 013 - Classification in Python | Titanic Dataset | Use of Different Machine Learning Algorithms with Cross Validation
titanic_gender_submission.csv
3.18 KB
titanic_test.csv
28 KB
titanic_train.csv
59.8 KB
DSR_1_sklearn_DT_GridSearch_and_RandomSearch_CV.html
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DSR_2_sklearn_DT_Monte_Carlo_CV.html
1.36 MB
DSR_3_sklearn_RandomForest_GridSearch_and_RandomSearch_CV.html
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DSR_4_sklearn_RandomForest_Monte_Carlo_CV.html
1.36 MB
DSR_5_sklearn_GradientBoost_GridSearch_and_RandomSearch_CV.html
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DSR_6_sklearn_GradientBoost_Monte_Carlo_CV.html
1.37 MB
DSR_7_sklearn_XGBoost_GridSearch_and_RandomSearch_CV.html
1.36 MB
DSR_8_sklearn_XGBoost_Monte_Carlo_CV.html
1.37 MB
DSR_9_sklearn_CatBoost_GridSearch_and_RandomSearch_CV.html
1.42 MB
DSR_10_sklearn_CatBoost_Monte_Carlo_CV.html
1.56 MB
DSR_11_sklearn_lightgbm_GridSearch_and_RandomSearch_CV.html
1.34 MB
DSR_12_sklearn_lightgbm_Monte_Carlo_CV.html
1.29 MB
DSR_13_Keras_TensorFlow.html
1.38 MB
DSR_14_SKLearn_Keras_TensorFlow.html
1.34 MB
DSR_15_SKLearn_Keras_TensorFlow_GridSearch_CV.html
1.28 MB
DSR_16_using-H2O.html
356 KB
DSR_17_using-TURICREATE.html
956 KB
Python.zip
27.1 MB
Programming Problem-Solution in Data Science 014 - Classification in R | Titanic Dataset | Use of Different Machine Learning Algorithms with Cross Validation
titanic_gender_submission.csv
3.18 KB
titanic_test.csv
28 KB
titanic_train.csv
59.8 KB
DSR_1_CARET_LDA_with_parameter_tuning.html
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DSR_2_CARET_QDA_with_parameter_tuning.html
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DSR_3_CARET_SVM_with_parameter_tuning.html
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DSR_4_CARET_PLS_PDA_with_parameter_tuning.html
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DSR_5_CARET_NB_with_parameter_tuning.html
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DSR_6_CARET_Bagging_with_parameter_tuning.html
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DSR_7_CARET_RF_with_parameter_tuning.html
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DSR_8_CARET_XGBoost_with_parameter_tuning.html
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DSR_9_CARET_NeuralNetwork_with_parameter_tuning.html
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DSR_10_Keras_Tensorflow_with_parameter_tuning.html
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DSR_11_CARET_LDA_with_parameter_tuning.html
2.67 MB
R.zip
39.6 MB
Programming Problem-Solution in Data Science 015 - Time Series Forecasting in Python | Airline Passenger Dataset | End-to-End Data Science Projects
international-airline-passengers.csv
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TSA_1_ARMA_statsmodels.html
603 KB
TSA_2_ARIMA_statsmodels-Copy1.html
727 KB
TSA_3_HoltWinters_Model.html
722 KB
TSA_4_SARIMAX_Model.html
800 KB
TSA_5_DeepLearning_LSTM_Model.html
651 KB
TSA_6_DeepLearning_CNN_Model.html
649 KB
TSA_7_DeepLearning_MLP_Model.html
650 KB
TSA_8_AR_statsmodels.html
544 KB
TSA_9_ARIMA_FirstOrderAutoRegressive_Model.html
800 KB
TSA_10_SARIMAX_SeasonalRandomWalk_Model.html
912 KB
TSA_11_SARIMAX_SeasonalRandomTrend_Model.html
879 KB
TSA_12_SARIMAX_Seasonal_AutoRegressive_Model.html
896 KB
Python.zip
8.25 MB
Programming Problem-Solution in Data Science 016 - Time Series Forecasting in R | Airline Passenger Dataset | End-to-End Data Science Projects
international-airline-passengers.csv
1.84 KB
TSA_1_LinearModel.html
570 KB
TSA_2_PolyModel_Order_One.html
571 KB
TSA_3_PolyModel_Order_Two.html
571 KB
TSA_4_PolyModel_Order_Three.html
572 KB
TSA_5_PolyModel_Order_Four.html
573 KB
TSA_6_PolyModel_Order_Five.html
574 KB
TSA_7_PolyModel_Order_Six.html
563 KB
TSA_8_LogarithimicModel.html
555 KB
TSA_9_HoltWintersModel.html
823 KB
TSA_10_FirstOrderAutoRegressiveModel.html
859 KB
TSA_11_RandomWalkAutoRegressiveModel.html
770 KB
TSA_12_DifferencedFirstOrderAutoRegressiveModel.html
775 KB
TSA_13_SimpleExponentialSmoothingModel.html
776 KB
TSA_14_LinearExponentialSmoothingModel.html
841 KB
TSA_15_DumpedTrendLinearExponentialSmoothingModel.html
849 KB
TSA_16_Auto_ARIMA_Model.html
850 KB
TSA_17_SeasonalARIMA_RandomWalkModel.html
842 KB
TSA_18_SeasonalARIMA_RandomTrendModel.html
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TSA_19_SeasonalARIMA_GeneralModel.html
832 KB
TSA_20_SeasonalARIMA.html
843 KB
TSA_21_NNetAR.html
938 KB
R.zip
13.9 MB
Programming Problem-Solution in Data Science 017 - Classification using Python & MySQL | Sonar Mines Dataset | End-to-End Applied Machine Learning & Data Science Projects
sonar.mines.data.csv
84.1 KB
Notebook-01.html
541 KB
Notebook-02.html
550 KB
Notebook-03.html
378 KB
Notebook-04.html
552 KB
Notebook-05.html
542 KB
Notebook-06.html
542 KB
Notebook-07.html
548 KB
Notebook-08.html
576 KB
Python.zip
13.8 MB
Programming Problem-Solution in Data Science 018 - Classification using R & MySQL | Sonar Mines Dataset | End-to-End Applied Machine Learning & Data Science Projects
sonar.mines.data.csv
84.1 KB
End-to-End Notebook - 001.html
343 KB
End-to-End Notebook - 002.html
346 KB
End-to-End Notebook - 003.html
347 KB
End-to-End Notebook - 004.html
380 KB
R.zip
354 KB
Programming Problem-Solution in Data Science 019 - Classification using Python & MySQL | Diabetes Dataset | End-to-End Applied Machine Learning & Data Science Projects
pima.indians.diabetes.data.csv
22.7 KB
End-to-End Notebook - 001.html
515 KB
End-to-End Notebook - 002.html
525 KB
End-to-End Notebook - 003.html
520 KB
End-to-End Notebook - 004.html
520 KB
End-to-End Notebook - 005.html
518 KB
End-to-End Notebook - 006.html
517 KB
End-to-End Notebook - 007.html
523 KB
End-to-End Notebook - 008.html
575 KB
End-to-End Notebook - 009.html
613 KB
Python.zip
33.6 MB
Programming Problem-Solution in Data Science 020 - Classification using R & MySQL | Diabetes Dataset | End-to-End Applied Machine Learning & Data Science Projects
pima.indians.diabetes.data.csv
22.7 KB
End-to-End Notebook - 001.html
336 KB
End-to-End Notebook - 002.html
333 KB
End-to-End Notebook - 003.html
336 KB
End-to-End Notebook - 004.html
373 KB
R.zip
360 KB
Programming Problem-Solution in Data Science 021 - Classification using Python & MySQL | IRIS Dataset | End-to-End Applied Machine Learning & Data Science Projects
iris.data.csv
4.44 KB
Data Science Recipe Notebook - 001.html
533 KB
Data Science Recipe Notebook - 002.html
555 KB
Data Science Recipe Notebook - 003.html
603 KB
Data Science Recipe Notebook - 004.html
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Data Science Recipe Notebook - 005.html
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Data Science Recipe Notebook - 006.html
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Data Science Recipe Notebook - 007.html
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Data Science Recipe Notebook - 008.html
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Data Science Recipe Notebook - 009.html
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Data Science Recipe Notebook - 010.html
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Data Science Recipe Notebook - 011.html
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Data Science Recipe Notebook - 012.html
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Data Science Recipe Notebook - 013.html
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Data Science Recipe Notebook - 014.html
553 KB
Data Science Recipe Notebook - 015.html
704 KB
Data Science Recipe Notebook - 016.html
807 KB
Python.zip
45.1 MB
Programming Problem-Solution in Data Science 022 - Classification using R & MySQL | IRIS Dataset | End-to-End Applied Machine Learning & Data Science Projects
iris.data.csv
4.44 KB
Data Science Notebook in R - 001.html
319 KB
Data Science Notebook in R - 002.html
336 KB
Data Science Notebook in R - 003.html
367 KB
Data Science Notebook in R - 004.html
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Data Science Notebook in R - 005.html
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Data Science Notebook in R - 006.html
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Data Science Notebook in R - 007.html
357 KB
Data Science Notebook in R - 008.html
355 KB
Data Science Notebook in R - 009.html
351 KB
R.zip
857 KB
Programming Problem-Solution in Data Science 023 - Applied Statistics with R for Beginners and Business Analysts
Notebook 1.1 - Addition.html
270 KB
Notebook 1.2 - Subtraction.html
270 KB
Notebook 1.3 - Multiplication.html
270 KB
Notebook 1.4 - Division.html
270 KB
Notebook 1.5 - Division.html
272 KB
Notebook 1.6 - Division.html
271 KB
Notebook 2.1 - Vector.html
275 KB
Notebook 2.2 - Vectorized Operations.html
289 KB
Notebook 2.3 - Matrices.html
288 KB
Notebook 2.4 - list and dataframe.html
289 KB
Notebook 3.1 - Control Flow using If-Else.html
273 KB
Notebook 3.2 - Control Flow using For Loop.html
271 KB
Notebook 3.3 - Control Flow using WHILE Loop.html
276 KB
Notebook 3.4 - Functions in R.html
277 KB
Notebook 4.1 - Central Tendency and Spread of Data.html
283 KB
Notebook 4.3 - Plotting of Data - Barplot.html
374 KB
Notebook 4.2 - Plotting of Data - Histogram.html
625 KB
Notebook 4.4 - Plotting of Data - Boxplot.html
766 KB
Notebook 4.5 - Plotting of Data - Scatterplot.html
564 KB
Notebook 5.2 - Hypothesis testing in R.html
280 KB
Notebook 5.1 - Distribution.html
310 KB
Notebook 5.3 - Statistical Simulation of Data in R.html
566 KB
Notebook 6.1 - OLS Regression in R.html
354 KB
Notebook 6.3 - Principle Component Regression in R.html
357 KB
Notebook 6.2 - Stepwise Regression in R.html
356 KB
Notebook 6.4 - Partial Least Square Regression in R.html
358 KB
Notebook 6.5 - Ordinary Least Square Regression in R.html
271 KB
Notebook 7.1 - Multiple Linear Regression in R.html
395 KB
Notebook 8.1 - One Way ANOVA Test.html
703 KB
Notebook 8.2 - Two Way ANOVA Test.html
742 KB
Notebook 9.3 - Histogram Chart.html
497 KB
Notebook 9.2 - Bar Chart.html
614 KB
Notebook 9.1 - Line Chart.html
721 KB
Notebook 9.4 - PIE Chart.html
462 KB
Notebook 9.5 - Dot Chart.html
398 KB
Notebook 10.2 - descriptive statistics with iris dataset.html
294 KB
Notebook 10.1 - descriptive statistics with mtcars dataset.html
306 KB
Notebook 10.3 - descriptive statistics with airquality dataset.html
432 KB
Notebook 10.4 - descriptive statistics with macroeconomic dataset.html
375 KB
Notebook 11.1 - Freq and Crosstabs with mtcars dataset.html
786 KB
Notebook 11.2 - Freq and Crosstabs with iris dataset.html
1.17 MB
Notebook 11.3 - Freq and Crosstabs with airquality dataset.html
1.24 MB
Notebook 12.1 - correlations with mtcars dataset.html
2.19 MB
Notebook 12.2 - correlations with iris dataset.html
1.56 MB
Notebook 12.3 - correlations with airquality dataset.html
1.53 MB
Notebook 13.1 - Basic Survival Analysis in R using Lung Dataset.html
731 KB
Notebook 13.2 - Advanced Survival Analysis in R using Lung Dataset.html
977 KB
Notebook 13.3 - Basic Survival Analysis in R using AML Dataset.html
550 KB
Notebook 13.4 - Advanced Survival Analysis in R using AML Dataset.html
704 KB
Notebook 13.5 - Basic Survival Analysis in R using cancer Dataset.html
732 KB
Notebook 13.6 - Advanced Survival Analysis in R using cancer Dataset.html
981 KB
Notebook 14.1 - TSA and Forecasting in R.html
3.27 MB
Notebook 14.2 - TSA and Forecasting with Airline Passenger Dataset in R.html
1.52 MB
Notebook 14.3 - TSA and Forecasting with JJ Sales Dataset in R.html
1.24 MB
Notebook 15.1 - Market Basket Analysis.html
612 KB
R.zip
42.2 MB
Programming Problem-Solution in Data Science 024 - Cluster Analysis in Python | Tree Leaf Dataset
plantDatasetforClusterAnalysis.csv
1.5 MB
CA_1_Agglomerative_Algorithm.html
1.69 MB
CA_2_KMeans_Algorithm.html
1.68 MB
CA_3_AffinityPropagation_Algorithm.html
1.69 MB
CA_4_DBSCAN_Algorithm.html
1.66 MB
CA_5_MeanShift_Algorithm.html
1.66 MB
CA_6_SpectralCustering_Algorithm.html
1.66 MB
CA_7_Birch_Algorithm.html
1.66 MB
CA_8_MiniBatchKMeans_Algorithm.html
1.67 MB
Python.zip
30.7 MB
Programming Problem-Solution in Data Science 025 - Cluster Analysis in R | IRIS Dataset
iris.data.csv
4.51 KB
CA_1_DistanceBasedClusterAnalysis.html
1.45 MB
CA_2_KMeans_and_PAM_BasedClusterAnalysis.html
3.88 MB
CA_3_CLARA_BasedClusterAnalysis.html
605 KB
CA_4_HierarchicalClusterAnalysis.html
794 KB
CA_5_AgglomerativeClusterAnalysis.html
2.38 MB
CA_6_HeatMapbasedClusterAnalysis.html
909 KB
R.zip
12.1 MB
Programming Problem-Solution in Data Science 026 - Regression in Python & MySQL | Ames Housing Price Dataset | Applied Machine Learning & Data Science Projects
Ameshousing.csv
936 KB
Notebook-01.html
1.07 MB
Notebook-02.html
976 KB
Notebook-03.html
1.07 MB
Notebook-04.html
1.1 MB
Notebook-05.html
1.06 MB
Notebook-06.html
952 KB
Notebook-07.html
1 MB
Notebook-08.html
938 KB
Notebook-09.html
940 KB
Python.zip
79.2 MB
Programming Problem-Solution in Data Science 027 - Regression in R & MySQL | Ames Housing Price Dataset | Applied Machine Learning & Data Science Projects
AmesHousing.csv
936 KB
Notebook-01.html
9.02 MB
Notebook-02.html
8.28 MB
Notebook-03.html
8.33 MB
R.zip
90.3 MB
Programming Problem-Solution in Data Science 028 - Regression in Python & MySQL | Boston Housing Price Dataset | Applied Machine Learning & Data Science Projects
boston.housing.data.csv
34.8 KB
Notebook-01.html
963 KB
Notebook-02.html
941 KB
Notebook-03.html
956 KB
Notebook-04.html
1.22 MB
Notebook-05.html
992 KB
Notebook-06.html
959 KB
Notebook-06.html
959 KB
Notebook-07.html
962 KB
Notebook-08.html
1.09 MB
Notebook-09.html
1.1 MB
Notebook-10.html
938 KB
Python.zip
75.1 MB
Programming Problem-Solution in Data Science 029 - Regression in R & MySQL | Boston Housing Price Dataset | Applied Machine Learning & Data Science Projects
boston.housing.data.csv
34.8 KB
Notebook-01.html
343 KB
Notebook-02.html
344 KB
Notebook-03.html
347 KB
R.zip
303 KB
Programming Problem-Solution in Data Science 030 - Tabular Data Analytics in R | Breast Cancer Dataset
BreastCancerWisconsin.data.csv
19.4 KB
program-xgboost.R.html
378 KB
program-Random Forest.R.html
373 KB
program-Neural Networks.R.html
377 KB
R.zip
236 KB
Programming Problem-Solution in Data Science 031 - Tabular Data Analytics in Python | Breast Cancer Dataset
BreastCancerWisconsin.data.csv
19.4 KB
project-sklrean-boosting.Python.html
419 KB
project-xgboost.Python.html
424 KB
project-lightgbm.Python.html
414 KB
project-DecisionTree.Python.html
427 KB
project-RandomForest.Python.html
420 KB
project-NB-KNN-SVM.Python.html
496 KB
Python.zip
6.08 MB
Programming Problem-Solution in Data Science 032 - Tabular Data Analytics in Python & R | Wine Quality Dataset
winequality.red.data.csv
82.2 KB
winequality.white.data.csv
258 KB
project-Predicting Wine Quality-MLP.Python.html
478 KB
project-Predicting Wine Quality-NB KNN.Python.html
478 KB
project-Predicting Wine Quality-LR.Python.html
440 KB
project-Predicting Wine Quality-GradientBoosting.Python.html
466 KB
project-Predicting Wine Quality-LightGBM.Python.html
469 KB
project-Predicting Wine Quality-XGBoost.Python.html
455 KB
project-Predicting Wine Quality-Random Forest.Python.html
467 KB
project-Predicting Wine Quality-Extra Trees.Python.html
467 KB
project-Predicting Wine Quality-Decision Tree.Python.html
480 KB
project-Predicting Wine Quality-A Comparison of Classifiers.Python.html
485 KB
predictingWineQuality-BoostingEnsembles_in_R.html
371 KB
predictingWineQuality-BaggingEnsembles_in_R.html
374 KB
predictingWineQuality-NeuralNetworks_in_R.html
382 KB
Python and R.zip
12.5 MB
Programming Problem-Solution in Data Science 033 - Tabular Data Analytics in Python and R | Adult Income Dataset
adult.income.data.csv
3.79 MB
project-01-comapring-sklearn-classifiers.Python.html
432 KB
project-comapring-sklearn-gradientboosting.Python.html
422 KB
project-comapring-xgboost.Python.html
417 KB
project-comapring-LIGHTGBM.Python.html
424 KB
project-comapring-DecisionTree.Python.html
429 KB
project-comapring-RandomForest.Python.html
423 KB
project-comapring-Neural Networks.Python.html
426 KB
PredictingIncome-BoostingEnsembles.R.html
355 KB
PredictingIncome-BaggingEnsembles.R.html
357 KB
PredictingIncome-NeuralNetworks.R.html
360 KB
Python and R.zip
107 MB
Programming Problem-Solution in Data Science 034 - Deep Learning in Python | Breast Cancer Dataset | Application of Tensorflow and Keras
BreastCancerWisconsin.data.csv
19.4 KB
DeepLearning01-UsingBreastCancerDataset.Python.html
375 KB
DeepLearning02-UsingBreastCancerDataset.Python.html
392 KB
DeepLearning03-UsingBreastCancerDataset.Python.html
382 KB
DeepLearning04-UsingBreastCancerDataset.Python.html
384 KB
DeepLearning05-UsingBreastCancerDataset.Python.html
385 KB
DeepLearning06-UsingBreastCancerDataset.Python.html
384 KB
DeepLearning07-UsingBreastCancerDataset.Python.html
387 KB
Python.zip
1.01 MB
Programming Problem-Solution in Data Science 035 - Deep Learning in Python | Sonar Dataset | Application of Tensorflow and Keras
sonar.mines.data.csv
84.1 KB
Project 01 - Deep Learning with Sonar Dataset.Python.html
390 KB
Project 02 - Deep Learning with Sonar Dataset.Python.html
389 KB
Project 03 - Deep Learning with Sonar Dataset.Python.html
388 KB
Project 04 - Deep Learning with Sonar Dataset.Python.html
386 KB
Project 05 - Deep Learning with Sonar Dataset.Python.html
386 KB
Project 06 - Deep Learning with Sonar Dataset.Python.html
393 KB
Python.zip
1.42 MB
Programming Problem-Solution in Data Science 036 - Deep Learning in Python | Diabetes Dataset | Application of Tensorflow and Keras
pima.indians.diabetes.data.csv
22.7 KB
Project 01 - Deep Learning with Diabetes Dataset.Python.html
389 KB
Project 02 - Deep Learning with Diabetes Dataset.Python.html
381 KB
Project 03 - Deep Learning with Diabetes Dataset.Python.html
382 KB
Project 04 - Deep Learning with Diabetes Dataset.Python.html
383 KB
Project 05 - Deep Learning with Diabetes Dataset.Python.html
385 KB
Project 06 - Deep Learning with Diabetes Dataset.Python.html
385 KB
Python.zip
945 KB
Programming Problem-Solution in Data Science 037 - Deep Learning in Python | Adult Income Dataset | Application of Tensorflow and Keras
adult.income.data.csv
3.79 MB
Project 01 - Deep Learning with Adult Income Dataset.Python.html
361 KB
Project 02 - Deep Learning with Adult Income Dataset.Python.html
361 KB
Project 03 - Deep Learning with Adult Income Dataset.Python.html
358 KB
Project 04 - Deep Learning with Adult Income Dataset.Python.html
357 KB
Project 05 - Deep Learning with Adult Income Dataset.Python.html
357 KB
Project 06 - Deep Learning with Adult Income Dataset.Python.html
364 KB
Python.zip
3.41 MB
Programming Problem-Solution in Data Science 038 - Deep Learning in Python | Ames Housing Dataset | Regression in Python | Application of Tensorflow and Keras
Project 01 - Deep Regression with Ames Housing Dataset.Python.html
415 KB
Ameshousing.csv
936 KB
Project 02 - Deep Regression with Ames Housing Dataset.Python.html
404 KB
Project 03 - Deep Regression with Ames Housing Dataset.Python.html
405 KB
Project 04 - Deep Regression with Ames Housing Dataset.Python.html
408 KB
Project 05 - Deep Regression with Ames Housing Dataset.Python.html
408 KB
Python.zip
4.53 MB
Programming Problem-Solution in Data Science 039 - Deep Regression with Boston Housing dataset in Python | Application of Tensorflow and Keras
housing.csv
47.9 KB
boston.housing.data.csv
47.9 KB
Project 01 - Deep Regression with Boston Housing Dataset.Python.html
410 KB
Project 02 - Deep Regression with Boston Housing Dataset.Python.html
398 KB
Project 03 - Deep Regression with Boston Housing Dataset.Python.html
399 KB
Project 04 - Deep Regression with Boston Housing Dataset.Python.html
403 KB
Project 05 - Deep Regression with Boston Housing Dataset.Python.html
403 KB
Python.zip
2.64 MB
Programming Problem-Solution in Data Science 040 - Deep Regression and Classification using Wine Quality Dataset | Python Data Science | Application of Tensorflow and Keras
winequality.data.csv
381 KB
Project 01 - Deep Regression and Classification using Wine Quality Dataset.py
44.2 KB
Project 02 - Deep Regression with Boston Housing Dataset.Python.html
437 KB
Project 03 - Deep Regression and Classification using Wine Quality Dataset.html
430 KB
Project 04 - Deep Regression and Classification using Wine Quality Dataset.html
429 KB
Project 05 - Deep Regression and Classification using Wine Quality Dataset.html
437 KB
Python.zip
7.96 MB
Programming Problem-Solution in Data Science 041 - Time Series Forecasting in R | Lynx Dataset
lynx.csv
1.17 KB
TSF_Project_01_Linear_model_in_R.R
2.41 KB
TSF_Project_02_Polynomial_model_Order_1_in_R.R
2.36 KB
TSF_Project_03_Polynomial_model_Order_2_in_R.R
2.33 KB
TSF_Project_04_Polynomial_model_Order_3_in_R.R
2.39 KB
TSF_Project_05_Polynomial_model_Order_4_in_R.R
2.45 KB
TSF_Project_06_Polynomial_model_Order_5_in_R.R
2.51 KB
TSF_Project_07_Polynomial_model_Order_6_in_R.R
2.55 KB
TSF_Project_08_Logarithmic_model_in_R.R
2.31 KB
TSF_Project_09_HoltWinters_model_in_R.R
2.68 KB
TSF_Project_10_First_Order_AutoRegressive_model_in_R.R
1.95 KB
TSF_Project_11_Random_Walk_model_in_R.R
1.86 KB
TSF_Project_12_Differenced_First_Ordered_AutoRegressive_model_in_R.R
2.15 KB
TSF_Project_13_Simple_Exponential_Smoothing_model_in_R.R
2.13 KB
TSF_Project_14_Linear_Exponential_Smoothing_model_in_R.R
2.13 KB
TSF_Project_15_Damped_Trend_Linear_Exponential_Smoothing_model_in_R.R
2.15 KB
TSF_Project_16_Auto_ARIMA_model_in_R.R
2.16 KB
TSF_Project_17_Seasonal_Random_Walk_model_in_R.R
2.18 KB
TSF_Project_18_Seasonal_ARIMA_model_in_R.R
2.17 KB
TSF_Project_19_Neural_Network_model_in_R.R
1.98 KB
TSF_Project_20_MLP_model_in_R.R
1.69 KB
R.zip
1.4 MB
Programming Problem-Solution in Data Science 042 - Time Series Forecasting in Python | Lynx Dataset
lynx.csv
1.17 KB
TSF-Project-01-ARMA_Model.py
4.9 KB
TSF-Project-02-ARIMA_Model.py
5.69 KB
TSF-Project-03-HoltWinters_Model.py
5.86 KB
TSF-Project-04-SARIMAX_Model.py
6.32 KB
TSF-Project-05-TF_LSTM_Model.py
5.53 KB
TSF-Project-06-TF_CNN_Model.py
5.81 KB
TSF-Project-07-TF_MLP_Model.py
5.71 KB
TSF-Project-08-First_Order_AR_Model.py
4.33 KB
TSF-Project-09-Seasonal_Random_Walk_Model.py
4.41 KB
TSF-Project-10-Seasonal_Random_Trend_Model.py
4.42 KB
Python.zip
1.31 MB
Programming Problem-Solution in Data Science 043 - Time Series Forecasting in R | Euro Stock Dataset
EuStockMarkets.csv
34.2 KB
project-01-Linear Model in R.R
2.35 KB
project-02-Polynomial Model in R.R
2.36 KB
project-03-Logarithimic Model in R.R
2.34 KB
project-04-HoltWinters Model in R.R
2.7 KB
project-05 - Auto ARIMA Model in R.R
2.18 KB
project-06 - Seasonal ARIMA Model in R.R
2.19 KB
project-07 - Neural Network Model in R.R
2.01 KB
R.zip
427 KB
Programming Problem-Solution in Data Science 044 - Time Series Forecasting in Python | Euro Stock Dataset
EuStockMarkets.csv
34.2 KB
TSF-Project-01-ARMA_Model.py
4.88 KB
TSF-Project-02-ARIMA_Model.py
4.2 KB
TSF-Project-03-SARIMA_Model.py
6.32 KB
TSF-Project-04-LSTM_Model.py
5.46 KB
TSF-Project-05-CNN_Model.py
5.83 KB
TSF-Project-06-MLP_Model.py
5.74 KB
Python.zip
271 KB
Programming Problem-Solution in Data Science 045 - Time Series Forecasting in R | Air Quality Dataset
AirQuality_Temp_Dataset.csv
2.25 KB
project-01-Linear Model in R.R
7.19 KB
project-02-Polynomial Model in R.R
7.8 KB
project-03-Logarithimic Model in R.R
2.35 KB
project-04-HoltWinters Model in R.R
2.79 KB
project-05-ARIMA Model in R.R
15 KB
project-06-SARIMA Model in R.R
7.13 KB
project-07-Neural Network Model in R.R
2.01 KB
R.zip
64 MB
Programming Problem-Solution in Data Science 046 - Time Series Forecasting in Python | Air Quality Dataset
AirQuality_Temp_Dataset.csv
2.25 KB
TSF-Project-01-ARMA_Model.py
4.9 KB
TSF-Project-02-ARIMA_Model.py
5.2 KB
TSF-Project-03-ETS_Model.py
5.32 KB
TSF-Project-04-SARIMAX_Model.py
6.32 KB
TSF-Project-05-LSTM_Model.py
5.42 KB
TSF-Project-06-CNN_Model.py
5.71 KB
Python.zip
53.3 MB
Programming Problem-Solution in Data Science 047 - Propensity Modelling in Python | Classification Projects | Telco Churn Dataset
TelcoCustomerChurnDataset.csv
294 KB
project-001.py
24.7 KB
project-002.py
27 KB
project-003.py
25.1 KB
project-004.py
27 KB
project-005.py
25.6 KB
project-006.py
27.6 KB
project-007.py
24.6 KB
project-008.py
27.2 KB
project-010.py
25.8 KB
project-011.py
23.2 KB
project-012.py
25.6 KB
project-013.py
22 KB
project-014.py
22.7 KB
project-016.py
21.5 KB
project-017.py
24.2 KB
project-018.py
18 KB
project-019.py
18 KB
project-020.py
17.9 KB
project-021.py
17.8 KB
Python.zip
19.6 MB
Programming Problem-Solution in Data Science 048 - Propensity Modelling in R | Classification Projects | Telco Churn Dataset
Project-1.R
15.3 KB
TelcoCustomerChurnDataset.csv
294 KB
Project-2.R
12.9 KB
Project-3.R
18.1 KB
Project-4.R
17.5 KB
Project-5.R
17.8 KB
Project-6.R
17.1 KB
Project-7.R
16.6 KB
Project-8.R
17.1 KB
Project-9.R
22.5 KB
Project-10.R
21 KB
Project-11.R
13.4 KB
Project-12.R
13.5 KB
Project-13.R
11.3 KB
R.zip
3.66 MB
Programming Problem-Solution in Data Science 049 - Propensity Modelling in Python | Classification Projects | Employee Churn Dataset
EmployeeChurnDataset.csv
554 KB
project-001.py
24.3 KB
project-002.py
26.3 KB
project-003.py
24.8 KB
project-004.py
26.3 KB
project-005.py
25.3 KB
project-006.py
26.9 KB
project-007.py
24.2 KB
project-008.py
26.5 KB
project-010.py
25.2 KB
project-011.py
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project-012.py
25 KB
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project-014.py
22.3 KB
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21.2 KB
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project-018.py
18.3 KB
project-019.py
18 KB
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project-021.py
17.8 KB
Python.zip
27.6 MB
Programming Problem-Solution in Data Science 050 - Propensity Modelling in R | Classification Projects | Employee Churn Dataset
EmployeeChurnDataset.csv
554 KB
Project-1.R
15 KB
Project-2.R
12.6 KB
Project-3.R
17.7 KB
Project-4.R
17.3 KB
Project-5.R
17.5 KB
Project-6.R
16.7 KB
Project-7.R
16.3 KB
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16.8 KB
Project-9.R
22.2 KB
Project-10.R
20.7 KB
Project-11.R
13.9 KB
Project-12.R
13.4 KB
Project-13.R
11.2 KB
R.zip
2.43 MB
Programming Problem-Solution in Data Science 051 - Propensity Modelling in Python | Classification Projects | Parkinson Dataset
ReplicatedAcousticFeatures-ParkinsonDatabase.csv
121 KB
project-01.py
24.8 KB
project-02.py
28.3 KB
project-03.py
25.2 KB
project-04.py
28.3 KB
project-05.py
25.7 KB
project-06.py
28.9 KB
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24.7 KB
project-08.py
28.6 KB
project-10.py
27.1 KB
project-11.py
23.2 KB
project-12.py
27 KB
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22 KB
project-14.py
22.7 KB
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25.6 KB
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21.8 KB
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project-21.py
18.4 KB
Python.zip
6.95 MB
Programming Problem-Solution in Data Science 052 - Propensity Modelling in R | Classification Projects | Parkinson Dataset
ReplicatedAcousticFeatures-ParkinsonDatabase.csv
121 KB
project-01.R
14.6 KB
project-02.R
12.4 KB
project-03.R
17.3 KB
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20.3 KB
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13.4 KB
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11.3 KB
R.zip
782 KB
Programming Problem-Solution in Data Science 053 - Propensity Modelling in Python | Machine Learning Classification | Bank Customer Churn Dataset
Bank_Customer_Churn_Modelling_Dataset.csv
669 KB
project-01.py
24.6 KB
project-02.py
26 KB
project-03.py
25 KB
project-04.py
26 KB
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25.5 KB
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24.9 KB
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23 KB
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24.7 KB
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21.8 KB
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22.5 KB
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25.4 KB
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18.4 KB
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18.3 KB
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18.2 KB
Python.zip
38.2 MB
Programming Problem-Solution in Data Science 054 - Propensity Modelling in R | Machine Learning Classification | Bank Customer Churn Dataset | Data Science Projects
Bank_Customer_Churn_Modelling_Dataset.csv
669 KB
project-01.R
15 KB
project-02.R
12.6 KB
project-03.R
17.7 KB
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17.2 KB
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20.5 KB
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13.3 KB
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11.1 KB
R.zip
3.34 MB
Programming Problem-Solution in Data Science 055 - Propensity Modelling in Python | Machine Learning Classification | Mobile Price Dataset | Data Science Projects
mobilePriceClassification_trainDataset.csv
120 KB
mobilePriceClassification_testDataset.csv
62.4 KB
project-01.py
25.8 KB
project-02.py
27.8 KB
project-03.py
26.3 KB
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27.9 KB
project-05.py
26.8 KB
project-06.py
28.5 KB
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25.7 KB
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28.2 KB
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26.8 KB
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24.4 KB
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26.6 KB
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23.6 KB
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24.4 KB
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27.3 KB
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22 KB
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24.4 KB
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21 KB
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20.9 KB
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20.8 KB
project-21.py
20.7 KB
Python.zip
38.7 MB
Programming Problem-Solution in Data Science 056 - Propensity Modelling in R | Machine Learning Classification | Mobile Price Dataset | Data Science Projects
mobilePriceClassification_trainDataset.csv
120 KB
mobilePriceClassification_testDataset.csv
62.4 KB
project-01.R
14.7 KB
project-02.R
12.5 KB
project-03.R
17.4 KB
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17.3 KB
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17.3 KB
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21.9 KB
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20.5 KB
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13.5 KB
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13.6 KB
project-13.R
11.1 KB
R.zip
966 KB
Programming Problem-Solution in Data Science 057: Machine Learning Classification in Python | Flower Dataset | Data Science for Beginners | Learn by Coding Projects
iris-species-dataset.csv
4.51 KB
project-01.py
20 KB
project-02.py
20.4 KB
project-03.py
18.2 KB
project-04.py
18.8 KB
project-05.py
18.2 KB
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18.8 KB
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17.1 KB
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18.4 KB
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16.1 KB
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17.4 KB
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16.2 KB
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17.3 KB
project-13.py
15.4 KB
Python.zip
4.23 MB
Programming Problem-Solution in Data Science 058 - Machine Learning Classification in R | Flower Dataset | Data Science for Beginners | Learn by Coding Projects
iris-species-dataset.csv
4.51 KB
project-01.R
18.5 KB
project-02.R
16.1 KB
project-03.R
21.2 KB
project-04.R
21 KB
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20.9 KB
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20.6 KB
project-07.R
22 KB
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20.7 KB
project-09.R
78.2 KB
R.zip
257 KB
Programming Problem-Solution in Data Science 059 - Machine Learning Classification in Python | Titanic Survival Dataset | Data Science for Beginners | Learn by Coding Projects
titanic_gender_submission.csv
3.18 KB
titanic_test.csv
28 KB
titanic_train.csv
59.8 KB
project-01.py
25.6 KB
project-02.py
25.9 KB
project-03.py
25.5 KB
project-04.py
26 KB
project-05.py
25.5 KB
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26 KB
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24.5 KB
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25.5 KB
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23.4 KB
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24.1 KB
project-11.py
23.4 KB
project-12.py
24.5 KB
project-13.py
22.8 KB
project-14.py
25.4 KB
Python.zip
11.7 MB
Programming Problem-Solution in Data Science 060 - Machine Learning Classification in R | Titanic Survival Dataset | Data Science for Beginners | Learn by Coding Projects
titanic_gender_submission.csv
3.18 KB
titanic_test.csv
28 KB
titanic_train.csv
59.8 KB
project-01.R
19.8 KB
project-02.R
17.6 KB
project-03.R
22.6 KB
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Programming Problem-Solution in Data Science 061: Machine Learning Classification in Python | London Dataset | Data Science for Beginners | Learn by Coding Projects
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Programming Problem-Solution in Data Science 062: Machine Learning Classification in R | London Dataset | Data Science for Beginners | Learn by Coding Projects
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Programming Problem-Solution in Data Science 063: Machine Learning Classification in Python | Breast Cancer Dataset | Data Science Projects for Beginners
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Programming Problem-Solution in Data Science 064: Machine Learning Classification in R | Breast Cancer Dataset | Data Science Projects for Beginners
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Programming Problem-Solution in Data Science 065: Machine Learning Classification in Python | Digit Recognition Dataset | Data Science Projects for Beginners
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Programming Problem-Solution in Data Science 066: Machine Learning Classification in R | Digit Recognition Dataset | Data Science Projects for Beginners
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Programming Problem-Solution in Data Science 067: Machine Learning Classification in Python | Credit Approval Dataset | Data Science Projects for Beginners
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Programming Problem-Solution in Data Science 068: Machine Learning Classification in R | Credit Approval Dataset | Data Science Projects for Beginners
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Programming Problem-Solution in Data Science 069: Kickstarter Examples - Deep Learning in Python
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Programming Problem-Solution in Data Science 070: Kickstarter Examples - Machine Learning in Python using Penn Machine Learning Benchmarks Datasets
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Programming Problem-Solution in Data Science 071: Machine Learning Classification in Python | AUS Credit Approval Dataset
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Programming Problem-Solution in Data Science 072: Machine Learning Classification in R | AUS Credit Approval Dataset
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Programming Problem-Solution in Data Science 073: Machine Learning Classification in Python | Edible Mushroom Dataset
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Programming Problem-Solution in Data Science 074: Machine Learning Classification in R | Edible Mushroom Dataset
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R.zip
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Programming Problem-Solution in Data Science 075: Machine Learning Classification in Python | Election Voting Dataset
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5.29 MB
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Programming Problem-Solution in Data Science 076: Machine Learning Classification in R | Election Voting Dataset
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Programming Problem-Solution in Data Science 077: Machine Learning Classification in Python | Glass Type Dataset
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Programming Problem-Solution in Data Science 078: Machine Learning Classification in R | Glass Type Dataset
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R.zip
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Programming Problem-Solution in Data Science 079: Machine Learning Classification in Python | Hepatitis Disease Dataset
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20.8 KB
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3.56 MB
Programming Problem-Solution in Data Science 080: Machine Learning Classification in R | Hepatitis Disease Dataset
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R.zip
126 KB
Programming Problem-Solution in Data Science 081: Applied Machine Learning Classification in Python | Lymphography Dataset
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Python.zip
4.12 MB
Programming Problem-Solution in Data Science 082: Applied Machine Learning Classification in R | Lymphography Dataset
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project-04-KNN-PLS-PDA-ParameterTuning.R
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project-06-BaggingEnsembles-ParameterTuning.R
19.9 KB
project-07-RandomForest-ParameterTuning.R
21.3 KB
project-08-BoostingEnsembles-ParameterTuning.R
20.1 KB
project-09-xgboost-ParameterTuning.R
24.8 KB
project-10-neural-networks-ParameterTuning.R
23.5 KB
project-11-Tensorflow-Keras-ParameterTuning.R
16.6 KB
project-12-Tensorflow-Keras-ParameterTuning.R
16.7 KB
R.zip
94.9 KB
Programming Problem-Solution in Data Science 083: Applied Machine Learning Classification in Python | Tumour Dataset
project-01-DecisioTree-GSCV.py
24.6 KB
project-03-RandomForest-GridSearchCV.py
25.2 KB
project-05-GBM-GridSearchCV.py
25.2 KB
project-07-xgboost-GridSearchCV.py
24.1 KB
project-09-catboost-GridSearchCV.py
22.8 KB
project-11-lightgbm-GridSearchCV.py
23.4 KB
project-13-TensorFlow-Keras.py
21.8 KB
project-14-TensorFlow-KerasClassifier-sklearn.py
22.3 KB
project-15-TensorFlow-Keras-GridSearchCV.py
25.6 KB
Python.zip
7.65 MB
Programming Problem-Solution in Data Science 084: Applied Machine Learning Classification in R | Tumour Dataset
project-01-LDA-ParameterTuning.R
18.3 KB
project-03-SVM-ParameterTuning.R
21.3 KB
project-04-KNN-PLS-PDA-ParameterTuning.R
21.1 KB
project-06-BaggingEnsembles-ParameterTuning.R
20.8 KB
project-07-RandomForest-ParameterTuning.R
22.1 KB
project-08-BoostingEnsembles-ParameterTuning.R
20.9 KB
project-09-xgboost-ParameterTuning.R
25.7 KB
project-10-neural-networks-ParameterTuning.R
24.2 KB
project-11-Tensorflow-Keras-ParameterTuning.R
15.8 KB
project-12-Tensorflow-Keras-ParameterTuning.R
15.8 KB
R.zip
98.8 KB