1- In the document named "Knn and Naive Bayes", you'll find 2 classifications methods (KNN and Naive Bayes) apply on 3 datasets (Iris Dataset, Monks Dataset, Congressional Voting Records Dataset) coded from scratch in Python without any Machine Learning library.

2- In the document named "Reinforcement Learning", you'll find the "UC Berkeley CS188 Intro to AI" 's pacman project: Q1: Value Iteration Q2: Bridge Crossing Analysis Q3: Policies Q4: Q-Learning Q5: Epsilon Greedy Q6: Bridge Crossing Revisited Q7: Q-Learning and Pacman Q8: Approximate Q-Learning