GitHub - nikhilniksss/Supervised-Machine-Learning: This Repository contains supervised machine learning algorithm implementations on python like KNN, Linear Regression, Logistic Regression, Naive Bayes, SVM, XGBoost etc.Also includes feature engineering techniques, handling missing data, data preprocessing using sklearn library.

nikhilniksss / Supervised-Machine-Learning Public

Notifications You must be signed in to change notification settings
Fork 0
Star 2

This Repository contains supervised machine learning algorithm implementations on python like KNN, Linear Regression, Logistic Regression, Naive Bayes, SVM, XGBoost etc.Also includes feature engineering techniques, handling missing data, data preprocessing using sklearn library.

2 stars 0 forks Branches Tags Activity

Star

Notifications

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 37 Commits
Decision Tree		Decision Tree
Grid Search based Decision Tree		Grid Search based Decision Tree
KNN		KNN
Linear Regression		Linear Regression
LinearRegression		LinearRegression
LogisticRegression		LogisticRegression
MLops		MLops
Multiple Linear Regression		Multiple Linear Regression
Naive Bayes		Naive Bayes
PCA based Decision Tree		PCA based Decision Tree
Polynomial Linear Regression		Polynomial Linear Regression
Practice set		Practice set
Randomforest based Decision Tree		Randomforest based Decision Tree
SVM		SVM
Stacking		Stacking
XGBoost		XGBoost
.DS_Store		.DS_Store
Feature_Engineering.ipynb		Feature_Engineering.ipynb
README.md		README.md
day_6_ridge_lasso.ipynb		day_6_ridge_lasso.ipynb
sk_data_preprocessing.ipynb		sk_data_preprocessing.ipynb
sk_feature_extraction.ipynb		sk_feature_extraction.ipynb
sk_missing_value.ipynb		sk_missing_value.ipynb
sk_nn.ipynb		sk_nn.ipynb
sk_parameter_search.ipynb		sk_parameter_search.ipynb
sklearn_ML.ipynb		sklearn_ML.ipynb