GitHub - babangain/Machine-Learning

I am revising Machine Learning Tutorials from all sources specifically A to Z Machine Learning Udemy.
Most of the data here belong to https://www.superdatascience.com/machine-learning/

Name		Name	Last commit message	Last commit date
Latest commit History 10 Commits
Activation_func_images		Activation_func_images
__pycache__		__pycache__
.gitattributes		.gitattributes
.gitignore		.gitignore
50_Startups.csv		50_Startups.csv
ANN.ipynb		ANN.ipynb
Activation Functions and cost functions.ipynb		Activation Functions and cost functions.ipynb
Ads_CTR_Optimisation.csv		Ads_CTR_Optimisation.csv
Apriori.ipynb		Apriori.ipynb
Churn_Modelling.csv		Churn_Modelling.csv
Classificaton-Pro-Cons.JPG		Classificaton-Pro-Cons.JPG
Clustering-Pro-Cons.JPG		Clustering-Pro-Cons.JPG
Comparisions.ipynb		Comparisions.ipynb
Decision Tree Classification.ipynb		Decision Tree Classification.ipynb
Decision Tree Regression.ipynb		Decision Tree Regression.ipynb
Eclat.ipynb		Eclat.ipynb
Grid Search.ipynb		Grid Search.ipynb
Hierarchical Clustering.ipynb		Hierarchical Clustering.ipynb
K Means Clustering.ipynb		K Means Clustering.ipynb
K fold cross Validation.ipynb		K fold cross Validation.ipynb
KNN.ipynb		KNN.ipynb
Kernel PCA.ipynb		Kernel PCA.ipynb
Kernel SVM.ipynb		Kernel SVM.ipynb
LDA.ipynb		LDA.ipynb
Linear Regression.ipynb		Linear Regression.ipynb
Logistic Regression.ipynb		Logistic Regression.ipynb
Mall_Customers.csv		Mall_Customers.csv
Market_Basket_Optimisation.csv		Market_Basket_Optimisation.csv
Multiple Linear Regression.ipynb		Multiple Linear Regression.ipynb
Naive Bayes.ipynb		Naive Bayes.ipynb
Natural Language Processing.ipynb		Natural Language Processing.ipynb
PCA.ipynb		PCA.ipynb
Polynomial Regression.ipynb		Polynomial Regression.ipynb
Position_Salaries.csv		Position_Salaries.csv
Random Forest Classification.ipynb		Random Forest Classification.ipynb
Random Forest Regression.ipynb		Random Forest Regression.ipynb
Regression Notes.ipynb		Regression Notes.ipynb
Regression-Pro-Cons.JPG		Regression-Pro-Cons.JPG
Restaurant_Reviews.tsv		Restaurant_Reviews.tsv
SVM.ipynb		SVM.ipynb
Salary_Data.csv		Salary_Data.csv
Social_Network_Ads.csv		Social_Network_Ads.csv
Stochastic_Gradient_Descent.png		Stochastic_Gradient_Descent.png
Support Vector Regression.ipynb		Support Vector Regression.ipynb
Thompson Sampling.ipynb		Thompson Sampling.ipynb
Thompson_Sampling_Baysian_Inference.png		Thompson_Sampling_Baysian_Inference.png
Thompson_Sampling_Slide.png		Thompson_Sampling_Slide.png
Thompson_vs_UCB.JPG		Thompson_vs_UCB.JPG
UCB_Algorithm_Slide.png		UCB_Algorithm_Slide.png
Upper Confidence Bound.ipynb		Upper Confidence Bound.ipynb
Wine.csv		Wine.csv
XGBoost.ipynb		XGBoost.ipynb
apyori.py		apyori.py
readme.md		readme.md

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