Python library that runs large language model inference layer by layer, so 70B-class models fit on a single 4GB GPU without quantization.
A 21-lesson Microsoft course teaching how to build generative AI applications, with code examples in Python and TypeScript.
Open-source Python framework for training and backtesting financial trading agents with deep reinforcement learning.
Example notebooks and guides showing how to accomplish common tasks with the OpenAI API.
A collection of 42+ runnable Jupyter notebooks, each tutorial covering an advanced technique for Retrieval-Augmented Generation systems.
MiniCPM5: SOTA on-device LLMs, small yet powerful.
Open-source AI-oriented quantitative investment platform covering data, strategy research, backtesting, simulated and live trading.
A collection of examples, tutorials, and apps for building with Liquid AI's open-weight LFM models and the LEAP SDK on laptops, mobile, and edge devices.
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
Open-source system where LLMs autonomously generate research ideas, run experiments, and write full scientific papers.
Open-source GPU cluster orchestrator and PyTorch-based framework for training LLMs with billions to trillions of parameters.
🚀 An open-source, hands-on curriculum bridging the gap from basic RL concepts to LLM alignment, RLVR, and advanced Agentic systems.
A neural network from OpenAI that scores how well text snippets match images, trained on image-text pairs for zero-shot prediction.
A beginner curriculum teaching the Model Context Protocol (MCP) with hands-on code examples in C#, Java, JavaScript, Rust, Python, and TypeScript.
Developer hub with training recipes, cookbooks, datasets, and end-to-end examples for building with NVIDIA's open Nemotron models.
Open-source large language models and tooling for financial tasks such as sentiment analysis, forecasting, and robo-advisory.
A collection of guides and examples for the Gemma open models from Google.
Sionna: An Open-Source Library for Research on Communication Systems
Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.
This repository showcases a selection of machine learning projects undertaken to understand and master various ML concepts. Each project reflects commitment to applying theoretical knowledge to practical scenarios, demonstrating proficiency in machine learning techniques and tools.
Agent memory for LLMs: 30 runnable Jupyter notebooks covering conversation buffers, vector stores, knowledge graphs, episodic and semantic memory, MemGPT, Mem0, Letta, Zep, Graphiti, LoCoMo benchmarks, and production patterns.
💿 Free software that works great, and also happens to be open-source Python.
Course notes & materials based on my CityU MSc CS journey. Includes study notes from 10 courses and resources shared by peers. Hope it helps fellow students — Star & PRs welcome. 基于香港城市大学 MSc CS 修课经历整理的课程笔记与资料。收录 10 门课程的学习沉淀,以及课程社群中同学们分享的资料。希望能帮到同样在学的同学,欢迎 Star 与 PR。
Learn OpenCV : C++ and Python Examples
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.
A collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like RF-DETR, YOLO11, SAM 3, and Qwen3-VL.
22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.
Open Machine Learning course
📚 Jupyter notebook tutorials for OpenVINO™
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Open-source AI cookbook
Notebooks & Example Apps for Search, Observability, and Security with Elasticsearch
This repository introduces PIXIU, an open-source resource featuring the first financial large language models (LLMs), instruction tuning data, and evaluation benchmarks to holistically assess financial LLMs. Our goal is to continually push forward the open-source development of financial artificial intelligence (AI).
This is a Phi Family of SLMs book for getting started with Phi Models. Phi a family of open sourced AI models developed by Microsoft. Phi models are the most capable and cost-effective small language models (SLMs) available, outperforming models of the same size and next size up across a variety of language, reasoning, coding, and math benchmarks
Gallery of OSMnx tutorials, usage examples, and feature demonstrations.
This repository provides an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses sophisticated graph based algorithm to handle the tasks.
A collection of notebooks/recipes showcasing usecases of open-source models with Together AI.
Probability and Statistics for Data Science: A self-contained introduction to probability and statistics for data science, including a free pdf, 103 Python notebooks using 23 real-world datasets, 118 videos with slides, and solutions to 200 exercises
🤗 Optimum Intel: Accelerate inference with Intel optimization tools
OpenCV for Unity (Untiy Asset Plugin)
Deep Learning Simplified is an Open-source repository, containing beginner to advance level deep learning projects for the contributors, who are willing to start their journey in Deep Learning. Devfolio URL, https://devfolio.co/projects/deep-learning-simplified-f013
Open quantum computing course for teaching, self-study, exam preparation, and quantum-technology career preparation.
—
The Classiq Library is the largest collection of quantum algorithms and applications. It is the best way to explore quantum computing software. We welcome community contributions to our Library 🙌
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.
Distill your LLM traces into a fast hybrid System 1 models. Open-source ML + LLM inference with calibrated deferral.
RadixQuantVLA is a unified, Lego-like framework for post-training quantization, benchmarking, and deployment preparation of Vision-Language-Action models, integrating QuantVLA, Omega-QVLA, OpenVLA, UniVLA, StarVLA, GR00T, and Pi0.5 routes with standardized launchers and validation on LIBERO benchmarks.