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1 NotebookIntroduction_Iris.ipynb
1 NotebookIntroduction_Iris.ipynb
 
 
10 Classification_ Social_Network_Ads.ipynb
10 Classification_ Social_Network_Ads.ipynb
 
 
11 Classification_Iris_PCA.ipynb
11 Classification_Iris_PCA.ipynb
 
 
12 Classification_Titanic.ipynb
12 Classification_Titanic.ipynb
 
 
13 Loan Risk Analysis_ class imbalance.ipynb
13 Loan Risk Analysis_ class imbalance.ipynb
 
 
14 Feature Scaling_ Standardization Normalization.ipynb
14 Feature Scaling_ Standardization Normalization.ipynb
 
 
2 mtcars_DataPreporcessing.ipynb
2 mtcars_DataPreporcessing.ipynb
 
 
3 Assignment1_ Soln_ Salaries.ipynb
3 Assignment1_ Soln_ Salaries.ipynb
 
 
4 Simple Linear Regression_ Salary.ipynb
4 Simple Linear Regression_ Salary.ipynb
 
 
5 Multiple Linear Regression.ipynb
5 Multiple Linear Regression.ipynb
 
 
50_Startups.csv
50_Startups.csv
 
 
6 Assignment_Boston Homes.ipynb
6 Assignment_Boston Homes.ipynb
 
 
7 polynomial_regression.ipynb
7 polynomial_regression.ipynb
 
 
8 Assignment__Advertising_9March.ipynb
8 Assignment__Advertising_9March.ipynb
 
 
9 Demo 2_ Bigmart.ipynb
9 Demo 2_ Bigmart.ipynb
 
 
9_v2 Demo 2_ Bigmart.ipynb
9_v2 Demo 2_ Bigmart.ipynb
 
 
Advertising.csv
Advertising.csv
 
 
IQR_Outliers.png
IQR_Outliers.png
 
 
IrisMissingData.csv
IrisMissingData.csv
 
 
Position_Salaries.csv
Position_Salaries.csv
 
 
README.md
README.md
 
 
Salaries.csv
Salaries.csv
 
 
Salary_Data.csv
Salary_Data.csv
 
 
Social_Network_Ads.csv
Social_Network_Ads.csv
 
 
bigmart_test.csv
bigmart_test.csv
 
 
bigmart_train.csv
bigmart_train.csv
 
 
iris-machinelearning.png
iris-machinelearning.png
 
 
iris_data_test.csv
iris_data_test.csv
 
 
iris_data_train.csv
iris_data_train.csv
 
 
loan_borowwer_data.csv
loan_borowwer_data.csv
 
 
mtcars.csv
mtcars.csv
 
 
rmse.png
rmse.png
 
 
titanicData.csv
titanicData.csv
 
 
train.csv
train.csv
 
 

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ML_course

Best for beginners | Well explained ML algorithms | organized Notebooks | Case Studies

  • This repository contains topic-wise Machine Learning hands-on notebooks.

  • It's for understanding fundamentals of Machine Learning in python.

  • Run these 1 to 14 .ipynb (python notebook) files in jupyter notebook.

Thanks :)

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Best for beginners | Well explained ML algorithms | organized Notebooks | Case Studies

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classificationcross-validationdata-scienceexploratory-data-analysisf1-scorefeature-engineeringfeature-selectionimbalanced-datamachine-learningoutlier-detectionprecisionrecallregressionsklearn-libraryvisualization

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