Stars
pytorch like baby neural net and reinforcement learning algorithms with scratch implementations
Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning for Qwen3.6, GPT-OSS, Llama, and more!
UniWorld: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation
Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math
FULL Augment Code, Claude Code, Cluely, CodeBuddy, Comet, Cursor, Devin AI, Junie, Kiro, Leap.new, Lovable, Manus, NotionAI, Orchids.app, Perplexity, Poke, Qoder, Replit, Same.dev, Trae, Traycer AI…
A chatbot using the RAG pipeline built with Django, Next.js 14, WebSockets, and powered by the LangChain framework. It leverages the llama2 model for processing user queries and generating responses.
Repo for the Deep Reinforcement Learning Nanodegree program
This is the official repository for The Hundred-Page Language Models Book by Andriy Burkov
A roadmap for "generative AI" learning resources
Question paper of courses taught at IISC as part of MTech AI curriculum
🐭 A tiny single-file implementation of Group Relative Policy Optimization (GRPO) as introduced by the DeepSeekMath paper
One click away from a locally downloaded, fine-tuned model, hosted on hugging face, with inference built in. In two hours.
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
FinRL®: Financial Reinforcement Learning. 🔥
Minimal reproduction of DeepSeek R1-Zero
Fully open reproduction of DeepSeek-R1
A curated list of reinforcement learning with human feedback resources (continually updated)
Reference implementation for DPO (Direct Preference Optimization)
Code for NeurIPS 2024 paper - The GAN is dead; long live the GAN! A Modern Baseline GAN - by Huang et al.
PyTorch implementations of Generative Adversarial Networks.
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
First-principle implementations of groundbreaking AI algorithms using a wide range of deep learning frameworks, accompanied by supporting research papers and demos.
FLUX, Stable Diffusion, SDXL, SD3, LoRA, Fine Tuning, DreamBooth, Training, Automatic1111, Forge WebUI, SwarmUI, DeepFake, TTS, Animation, Text To Video, Tutorials, Guides, Lectures, Courses, Comfy…
A nanoGPT pipeline packed in a spreadsheet
The most cited deep learning papers
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
just me trying to implement deep learning concepts in code