MachineLearning

This repository contains notebooks to study and prepare various concepts of Machine Learning from basics to advanced.

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Name		Name	Last commit message	Last commit date
Latest commit History 53 Commits
01. Data preprocessing.ipynb		01. Data preprocessing.ipynb
02. Simple Linear Regression.ipynb		02. Simple Linear Regression.ipynb
03. Multiple Linear Regression.ipynb		03. Multiple Linear Regression.ipynb
04. Polynomial Regression.ipynb		04. Polynomial Regression.ipynb
05. SVM Regression.ipynb		05. SVM Regression.ipynb
06. Decision Trees Regression.ipynb		06. Decision Trees Regression.ipynb
07. Random Forest Regression.ipynb		07. Random Forest Regression.ipynb
08. Logistic Regression Classification.ipynb		08. Logistic Regression Classification.ipynb
09. K-Nearest Neighbor(K-NN).ipynb		09. K-Nearest Neighbor(K-NN).ipynb
10. Support Vector Machine(SVM) Classification.ipynb		10. Support Vector Machine(SVM) Classification.ipynb
11. Kernel SVM Classification.ipynb		11. Kernel SVM Classification.ipynb
12. Naive Bayes Classification.ipynb		12. Naive Bayes Classification.ipynb
13. Decision Tree Classification.ipynb		13. Decision Tree Classification.ipynb
14. Random Forest Classification.ipynb		14. Random Forest Classification.ipynb
15. Metrics for Evaluation.ipynb		15. Metrics for Evaluation.ipynb
16. K-fold Cross Validation.ipynb		16. K-fold Cross Validation.ipynb
17. GridSeachCV.ipynb		17. GridSeachCV.ipynb
README.md		README.md