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Bayesian optimization in PyTorch

🛠 All-in-one web-based IDE specialized for machine learning and data science.

A library of data loaders for LLMs made by the community -- to be used with LlamaIndex and/or LangChain

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

Amazon Bedrock Agentcore accelerates AI agents into production with the scale, reliability, and security, critical to real-world deployment.

The hub for EleutherAI's work on interpretability and learning dynamics

Learn to build your Second Brain AI assistant with LLMs, agents, RAG, fine-tuning, LLMOps and AI systems techniques.

A library for debugging/inspecting machine learning classifiers and explaining their predictions

Benchmarking large language models' complex reasoning ability with chain-of-thought prompting

Model API for GALACTICA

FMA: A Dataset For Music Analysis

This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems.

Algorithms for outlier, adversarial and drift detection

Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.

Awesome resources for in-context learning and prompt engineering: Mastery of the LLMs such as ChatGPT, GPT-3, and FlanT5, with up-to-date and cutting-edge updates.

《面向开发者的 ChatGPT 提示词工程》非官方版中英双语字幕 Unofficial subtitles of "ChatGPT Prompt Engineering for Developers"

New ways of breaking app-integrated LLMs

Natural Gradient Boosting for Probabilistic Prediction

Python library for interactive topic model visualization. Port of the R LDAvis package.

Practical course about Large Language Models.

WFGY is heading toward WFGY 5.0 Polaris Protocol, a major open-source release for AI reasoning, RAG, agents, and real-world workflows. Includes Problem Map, Global Debug Card, WFGY 4.0, and the CFV Easter Egg.

A comprehensive guide to understanding and implementing large language models with hands-on examples using LangChain for GenAI applications.

Code for the paper "ViperGPT: Visual Inference via Python Execution for Reasoning"

Synthetic data generators for tabular and time-series data

Implementation of all RL algorithms in a simpler way

KoAlpaca: 한국어 명령어를 이해하는 오픈소스 언어모델 (KoAlpaca: An open-source language model to understand Korean instructions)

The official code repository for the second edition of the O'Reilly book Generative Deep Learning: Teaching Machines to Paint, Write, Compose and Play.

Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph. This is the companion repository for the book on generative AI with LangChain.