Machine-Learning-Tutorials

Why we included this project

This is a topic-wise index of machine learning and deep learning tutorials that has been maintained and expanded since 2015. Instead of a flat list of links, it groups resources by subject, from linear and logistic regression, SVMs, decision trees and boosting to deep learning topics like CNNs, RNNs/LSTM, autoencoders and graph representation learning, plus NLP, computer vision and reinforcement learning. That organization makes it a practical study map: if you are self-teaching or preparing for interviews, you can follow a coherent path instead of guessing what to read next. It also collects interview questions, cheat sheets, and pointers to courses, blogs, and Quora and Kaggle discussions, so it works as a companion reference while you build hands-on skills. For anyone putting together a learning curriculum or mentoring others, this list saves a lot of hunting.