Various Statistical and Machine Learning Algorithms, mainly from the ISLR book and datasets.
Topics: Linear Regression, Logistic Regression, Trees & Random Forest, KNN, SVM etc. In addition to important Machine Learning methods such as Cross-Validation, Model & Feature Selection, Regularization.
All the models are initially implemented from scratch, and later using the prebuilt libraries. (c) Dean Shabi
https://www-bcf.usc.edu/~gareth/ISL/
