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Boosting Section.ipynb
Boosting Section.ipynb
 
 
Classification of Text.ipynb
Classification of Text.ipynb
 
 
Cross Validation and Linear Regression Project.ipynb
Cross Validation and Linear Regression Project.ipynb
 
 
Dealing With Categorical Data.ipynb
Dealing With Categorical Data.ipynb
 
 
Decision Tree Learning.ipynb
Decision Tree Learning.ipynb
 
 
Extracting Features from Text Data.ipynb
Extracting Features from Text Data.ipynb
 
 
Feature scalling.ipynb
Feature scalling.ipynb
 
 
Gradient Boosting.ipynb
Gradient Boosting.ipynb
 
 
Grid Search.ipynb
Grid Search.ipynb
 
 
Introduction to KNN Section.ipynb
Introduction to KNN Section.ipynb
 
 
Introduction to feature engineering and data preparation.ipynb
Introduction to feature engineering and data preparation.ipynb
 
 
K-Mean Clustering.ipynb
K-Mean Clustering.ipynb
 
 
K-mean Color Quantization.ipynb
K-mean Color Quantization.ipynb
 
 
Linear Regression Project.ipynb
Linear Regression Project.ipynb
 
 
Linear Regression.ipynb
Linear Regression.ipynb
 
 
Logistic Regression-- Classification Performance Metrics.ipynb
Logistic Regression-- Classification Performance Metrics.ipynb
 
 
Logistic Regression--Multi-Class Problems.ipynb
Logistic Regression--Multi-Class Problems.ipynb
 
 
Logistic Regression.ipynb
Logistic Regression.ipynb
 
 
Natural Language Processing.ipynb
Natural Language Processing.ipynb
 
 
Polynomial Regression.ipynb
Polynomial Regression.ipynb
 
 
README.md
README.md
 
 
Random Forest Section part 1.ipynb
Random Forest Section part 1.ipynb
 
 
Random Forest Classifier part 2.ipynb
Random Forest Classifier part 2.ipynb
 
 
Random Forest Regressor.ipynb
Random Forest Regressor.ipynb
 
 
Regression Types.ipynb
Regression Types.ipynb
 
 
Regression with SVM.ipynb
Regression with SVM.ipynb
 
 
Scikit Learn .ipynb
Scikit Learn .ipynb
 
 
Support Vector Machine.ipynb
Support Vector Machine.ipynb
 
 

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Machine-Learning-Interoduction

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