A-Collection-of-great-ML-resources

This is a list of resources which have helped me understand various Machine Learning concepts. I hope to start from basic ideas like Linear Regression, Logistic Regression, etc. and move upto resources that cover more advanced topics like Neural Networks, RNNs, and CNNs

• Python Basics

  • Numpy
    • CS231n Numpy Tutorial
    • Numpy Official User Guide

• Regression

  • Linear Regression
    • Linear Regression videos from the ML course by Andrew Ng
    • StatQuest : Linear Regression clearly explained
    • ML Cheatsheet : Linear Regression
  • Logistic Regression
    • StatQuest : Logistic Regression
    • ML Cheatsheet : Logistic Regression

• Support Vector Machines

  • MIT OCW : SVM Lecture by Patrick Winston
  • SVM videos from the ML course by Andrew Ng
  • TDS introduction to SVMs
  • SVMs all you need to know

• Principal Component Analysis

  • StatQuest : PCA, Step-by-Step
  • An explanation of steps involved in PCA Computation