Popular GitHub Repositories for Markov Decision Process

Jobs_Applier_AI_Agent_AIHawk aims to easy job hunt process by automating the job application process. Utilizing artificial intelligence, it enables users to apply for multiple jobs in a tailored way.

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

Machine learning, in numpy

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

A video translation and dubbing tool powered by LLMs, offering professional-grade translations and one-click full-process deployment. It can generate content optimized for platforms like YouTube，TikTok, and Shorts. 基于AI大模型的视频翻译和配音工具，专业级翻译，一键部署全流程，可以生成适配抖音，小红书，哔哩哔哩，视频号，TikTok，Youtube Shorts等形态的内容

A video translation and dubbing tool powered by LLMs, offering professional-grade translations and one-click full-process deployment. It can generate content optimized for platforms like YouTube，TikTok, and Shorts. 基于AI大模型的视频翻译和配音工具，专业级翻译，一键部署全流程，可以生成适配抖音，小红书，哔哩哔哩，视频号，TikTok，Youtube Shorts等形态的内容

Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

The first AI agent that builds permissionless integrations through reverse engineering platforms' internal APIs.

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.

An extensive node suite that enables ComfyUI to process 3D inputs (Mesh & UV Texture, etc) using cutting edge algorithms (3DGS, NeRF, etc.)

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

MiniMax-01 is a simple implementation of the MiniMax algorithm, a widely used strategy for decision-making in two-player turn-based games like Tic-Tac-Toe. The algorithm aims to minimize the maximum possible loss for the player, making it a popular choice for developing AI opponents in various game scenarios.

A python library for decision tree visualization and model interpretation.

AI-powered Smart Robotic Process Automation ?

A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

A minimalist environment for decision-making in autonomous driving

[ICLR 2023] ReAct: Synergizing Reasoning and Acting in Language Models