The full collection of Jupyter Notebook labs from Andrew Ng's Machine Learning Specialization.

The Machine Learning project including ML/DL projects, notebooks, cheat codes of ML/DL, useful information on AI/AGI and codes or snippets/scripts/tasks with tips.

Implementation notebooks and scripts of Deep Reinforcement learning Algorithms in PyTorch and TensorFlow.

Sutton and Barto's RL Book Exercises in Jupiter Notebook (Python3)

A repository dedicated to learning about Artificial Intelligence, Machine Learning, and Deep Learning using Python/IPython Notebook.

collection of examples

jupyter notebook (python code) for sutton book

This repository contains the Jupyter Notebook (TreasureHuntGame.ipynb) for the Pirate Intelligent Agent project. The notebook demonstrates how I applied reinforcement learning and neural networks to solve a pathfinding problem, training a pirate NPC to find treasure before a human player can.

It features a 2D race car model using Reinforcement Learning to identify the fastest track path, showcased in a Jupyter Notebook.

This work is about creating a DQN agent, able to learn and well perform in the Atari2600 Pong, using Reinfrocement Learning and Deep Q-Network. The code is developed on a jupyter notebook in python while the game environment is provided by OpenAi called "OpenAi Gym".

A comprehensive collection of Reinforcement Learning Algorithms implemented in Jupyter Notebook aimed to provide clear, practical, and well-documented code for foundational algorithms.

The current repository contains Jupytre-notebook implementations of different Reinforcement Learning algorithms from the well-known Introduction to Reinforcement Learning book by Sutton & Barto, and algorithms from iconic papers in the field.

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.