Implementations of a few regressors and classifiers using only numpy for my course

Implemented

• Ridge Regressor: Linear Regression with ridge regularization (l2 regularization)
• Batch Gradient Descent Linear Regression
• Stochastic Gradient Descent
• Lasso Regression, with Feature Selection (l1 regularization)

• Naive Bayes Classification, using a Gaussian Distribution
• Logistic Regression using stochastic gradient descent
• Neural Network with a single hidden layer and a sigmoid transfer
• K-fold Cross Validation for hyperparameter tuning
• Kernel Logistic Regression using both linear and Hamming distance kernels