Notebook for quick search

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

📓 4월 알고리즘 스터디

This is the implementation of 3rd Part in 3-Part Series of Algorithms Illuminated Book. All Implementations in this repository are written in both Python and Golang. Single IPython Notebook contains all Algorithms given in this Part 3.

Notes and explorations in AI and other things

This notebook serves as an introduction to Linear Programming and MILP with Python, covering both the concepts and practical applications through various popular optimization problems.

Contains my learnings in the form of python notebooks

Coursera Reinforcement Learning Specialization by University of Alberta.

Contains notebook implementations for the AI based assignments using graph based algorithms that are commonly used in solving AI based problems. Algorithms include BFS, DFS, Hill Climbing, Differential Evolution, Genetic, Back Tracking..

Jupyter notebooks implementing Reinforcement Learning algorithms in Numpy and Tensorflow

Dynamic programming, Backtracking and Brute force algorithms. Made in C++ and experimented with Jupyter Notebook

Google Colab Notebooks for Udacity CS344 - Intro to Parallel Programming

Minimal implementation of Tic Tac Toe AI using MiniMax algorithm in Python with interface for jupyter notebook using ipywidgets

This repo contains several jupyter notebooks that implements some RL/DP algos with OpenAI Gym games. It also serves as my notes for Lehigh ISE416 dynamic programming.

This repository contains a practical application of Infinite Horizon Dynamic Programming (IHDP) techniques, demonstrated through the Frozen Lake environment and grid world examples. The repository includes a Jupyter Notebook that explores these techniques with visual aids.

This repository explores deterministic dynamic programming solutions for the Shortest Path Problem (SPP) and the Traveling Salesperson Problem (TSP). It includes graphical representations, a detailed Jupyter notebook, and practical implementations for optimizing travel routes and minimizing costs in various city-based scenarios.