Popular GitHub Repositories for Brain Graph Analysis

Build and share delightful machine learning apps, all in Python. ? Star to support our work!

Easily train a good VC model with voice data <= 10 mins!

Cross-platform, customizable ML solutions for live and streaming media.

Your AI second brain. Self-hostable. Get answers from the web or your docs. Build custom agents, schedule automations, do deep research. Turn any online or local LLM into your personal, autonomous AI (gpt, claude, gemini, llama, qwen, mistral). Get started - free.

Roadmap to becoming an Artificial Intelligence Expert in 2022

Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

SoftVC VITS Singing Voice Conversion

State-of-the-art 2D and 3D Face Analysis Project

Graph Neural Network Library for PyTorch

? A ranked list of awesome machine learning Python libraries. Updated weekly.

Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.

A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python

Turns Data and AI algorithms into production-ready web applications in no time.

Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced analytics with timeline and execution graph view

? GPU accelerated Neural networks in JavaScript for Browsers and Node.js

A toolkit for making real world machine learning and data analysis applications in C++

Python package built to ease deep learning on graph, on top of existing DL frameworks.

? Easy-to-use and powerful NLP and LLM library with ? Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including ?Text Classification, ? Neural Search, ? Question Answering, ?? Information Extraction, ? Document Intelligence, ? Sentiment Analysis etc.

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!