Scikit_Learn_FC

This is the full course of scikit-learn, which contains most used features.

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
L1 Linear Regression Single Variables		L1 Linear Regression Single Variables
L10 Random Forest		L10 Random Forest
L11 K Fold Cross Validation		L11 K Fold Cross Validation
L12 K Means Clustering Algorithm		L12 K Means Clustering Algorithm
L13 Naive Bayes Classifier Algorithm		L13 Naive Bayes Classifier Algorithm
L14 Hyper parameter Tuning (GridSearchCV)		L14 Hyper parameter Tuning (GridSearchCV)
L15 L1 and L2 Regularization		L15 L1 and L2 Regularization
L16 K nearest neighbors classification		L16 K nearest neighbors classification
L17 Principal Component Analysis (PCA)		L17 Principal Component Analysis (PCA)
L18 Ensemble Learning - Bagging		L18 Ensemble Learning - Bagging
L2 Linear Regression Multiple Variables		L2 Linear Regression Multiple Variables
L3 Gradient Descent and Cost Function		L3 Gradient Descent and Cost Function
L4 Save Model Using Joblib and Pickle		L4 Save Model Using Joblib and Pickle
L5 Dummy Variables & One Hot Encoding		L5 Dummy Variables & One Hot Encoding
L6 Training and Testing Data		L6 Training and Testing Data
L7 Logistic Regression		L7 Logistic Regression
L8 Decision Tree		L8 Decision Tree
L9 Support Vector Machine		L9 Support Vector Machine
Real Estate Price Prediction		Real Estate Price Prediction
SportsPersonClassifier		SportsPersonClassifier
.gitattributes		.gitattributes
README.md		README.md

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