A Bayesian global optimization package for material design | Adaptive Learning | Active Learning
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Updated
Oct 12, 2024 - Jupyter Notebook
A Bayesian global optimization package for material design | Adaptive Learning | Active Learning
Repository of Online Learning algorithms, including Bandits, UCB, and more.
该仓库包含基于 PyWebIO 的 UCB(上置信界)算法 在线演示,UCB 算法常用于多臂老虎机问题,以优化决策并最大化累积奖励。演示包括自动 UCB 算法模拟和交互式手动策略对比。
This repository contains an implementation of checkers where different agents play against each other using different algorithms including Monte Carlo Tree Search, Alpha-Beta Pruning, and Minimax.
Reinforcement learning used in the game of pong
LoRa@FIIT algorithms comparison using jupyter notebooks
Using SciKit Learn few Deep Learning Rules and Algorithms are implemented
Code for the paper "Truncated LinUCB for Stochastic Linear Bandits"
Predicting the best Ad from the given Ads.
This repo contains code templates of all the machine learning algorithms that are used, like Regression, Classification, Clustering, etc.
In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.
A novel parallel UCT algorithm with linear speedup and negligible performance loss.
Web visualisation of the k-armed bandit problem
Offline evaluation of multi-armed bandit algorithms
We compare different policies for the checkers game using reinforcement learning algorithms.
Checking CTR(Click Thorugh Rate) of an ad using Thompson Sampling (Reinforcement Lrearning)
We implemented a Monte Carlo Tree Search (MCTS) from scratch and we successfully applied it to Tic-Tac-Toe game.
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