lyogavin / airllm
Python library that runs large language model inference layer by layer, so 70B-class models fit on a single 4GB GPU without quantization.
lyogavin / airllm
microsoft / generative-ai-for-beginners
A 21-lesson Microsoft course teaching how to build generative AI applications, with code examples in Python and TypeScript.
microsoft / ai-agents-for-beginners
An 18-lesson beginner course with code samples on building AI agents using Microsoft's agent frameworks and services.
jackfrued / Python-100-Days
A free Chinese-language 100-day Python course, from basics to advanced topics, with lessons and code examples.
HandsOnLLM / Hands-On-Large-Language-Models
Code examples for the O'Reilly book Hands-On Large Language Models, covering LLM concepts and practical techniques in Jupyter notebooks.
GrEarl / microgpt-lesson
高校生向けLLM教材: Karpathy microgptベース，Google Colab用
microsoft / AI-For-Beginners
A 12-week, 24-lesson beginner curriculum covering AI fundamentals, neural networks, computer vision, NLP, and AI ethics with TensorFlow and PyTorch labs.
anthropics / claude-cookbooks
Jupyter notebooks and recipes demonstrating code patterns for building with the Claude API, including tool use, RAG, vision, and evaluations.
chiphuyen / aie-book
Companion repository for Chip Huyen's book AI Engineering, with chapter summaries, study notes, prompt examples, and case studies.
AI4Finance-Foundation / FinRL
Open-source Python framework for training and backtesting financial trading agents with deep reinforcement learning.
microsoft / ML-For-Beginners
A 12-week, 26-lesson beginner curriculum on classic machine learning using Scikit-learn, with quizzes and projects in Python and R.
stefan-jansen / machine-learning-for-trading
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
OpenBMB / MiniCPM
MiniCPM5: SOTA on-device LLMs, small yet powerful.
UFund-Me / Qbot
Open-source AI-oriented quantitative investment platform covering data, strategy research, backtesting, simulated and live trading.
udlbook / udlbook
Source repository for Simon Prince's textbook Understanding Deep Learning, with LaTeX sources, figures, and Jupyter notebooks.
The-Art-of-Hacking / h4cker
This repository is maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), AI security, vulnerability research, exploit development, reverse engineering, and more. 🔥 Also check: https://hackertraining.org
NVIDIA / accelerated-computing-hub
NVIDIA's curated collection of interactive GPU computing tutorials, syllabi, and guides covering CUDA, Python, and accelerated libraries.
SakanaAI / AI-Scientist
Open-source system where LLMs autonomously generate research ideas, run experiments, and write full scientific papers.
facebookresearch / audiocraft
PyTorch library for audio generation research, providing inference and training code for MusicGen, AudioGen, and EnCodec.
higgsfield-ai / higgsfield
Open-source GPU cluster orchestrator and PyTorch-based framework for training LLMs with billions to trillions of parameters.
walkinglabs / hands-on-modern-rl
🚀 An open-source, hands-on curriculum bridging the gap from basic RL concepts to LLM alignment, RLVR, and advanced Agentic systems.
microsoft / Data-Science-For-Beginners
A 10-week, 20-lesson beginner curriculum teaching data science through project-based lessons with quizzes and assignments.
microsoft / mcp-for-beginners
A beginner curriculum teaching the Model Context Protocol (MCP) with hands-on code examples in C#, Java, JavaScript, Rust, Python, and TypeScript.
DataTalksClub / machine-learning-zoomcamp
A free, cohort-based course teaching ML engineering: training models, exposing them via APIs, and deploying with Docker, Kubernetes, and AWS Lambda.
NVIDIA-NeMo / Nemotron
Developer hub with training recipes, cookbooks, datasets, and end-to-end examples for building with NVIDIA's open Nemotron models.
ageron / handson-ml3
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
charliedream1 / ai_quant_trade
Stock AI Trader: 1-stop platform for learning, sim & live trading. Covers: stock basics, strategies, LLMs, factor mining, ML/DL/RL, graph nets, HFT, C++ deploy & JoinQuant code. 股票AI操盘手：一站式学习、模拟、实盘平台。涵盖：股票基础、策略、大模型、因子挖掘、机器学习/深度学习/强化学习、图网络、高频交易、C++部署及聚宽代码。
rasbt / reasoning-from-scratch
Implement a reasoning LLM in PyTorch from scratch, step by step
AI4Finance-Foundation / FinGPT
Open-source large language models and tooling for financial tasks such as sentiment analysis, forecasting, and robo-advisory.
hoochanlon / hamuleite
🌊深度整合全球顶尖学术、金融与教育资源：学术板块汇聚 JSTOR、Taylor & Francis、剑桥大学出版社等权威平台的论文，并接入 Z-Library 影子图书馆的海量电子书；教育板块收录香港、新加坡从小学到高中以及大学学科教科书；金融板块则聚合香橼、摩根、野村等顶级机构的深度研报，只为打破信息孤岛，构建知识平权普惠知识库。
FinanceFlash / unvibecode
Complex code hides connections, workflows, and business risks.Unvibe complex code. Trace business workflows.
ageron / handson-mlp
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, PyTorch, and Hugging Face libraries.
datawhalechina / llm-algo-leetcode
LLM algorithm practice lab with theory, solutions, and test cases.《大模型算法与系统教程》面向大模型入门到进阶的算法实战教程，覆盖原理讲解、答案解析、测试用例与 CUDA/Triton 实战。
NVlabs / sionna
Sionna: An Open-Source Library for Research on Communication Systems
py-why / EconML
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.
esokolov / ml-course-hse
Машинное обучение на ФКН ВШЭ
genieincodebottle / generative-ai
Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.
NirDiamant / Agent_Memory_Techniques
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.
datawhalechina / base-llm
从 NLP 到 LLM 的算法全栈教程，在线阅读地址：https://datawhalechina.github.io/base-llm/
AllenDowney / ElementsOfDataScience
An introduction to data science in Python, for people with no programming experience.
mahmoud / awesome-python-applications
💿 Free software that works great, and also happens to be open-source Python.
borglab / gtsam
GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.
microsoft / edgeai-for-beginners
This course is designed to guide beginners through the exciting world of Edge AI, covering fundamental concepts, popular models, inference techniques, device-specific applications, model optimization, and the development of intelligent Edge AI agents.
lavine888 / CityU-CS-Notes
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。
microsoft / TinyTroupe
LLM-powered multiagent persona simulation for imagination enhancement and business insights.
TingsongYu / PyTorch-Tutorial-2nd
《Pytorch实用教程》（第二版）无论是零基础入门，还是CV、NLP、LLM项目应用，或是进阶工程化部署落地，在这里都有。相信在本书的帮助下，读者将能够轻松掌握 PyTorch 的使用，成为一名优秀的深度学习工程师。
AllenDowney / ThinkPython
Jupyter notebooks and other resources for Think Python by Allen Downey, published by O'Reilly Media.
benman1 / generative_ai_with_langchain
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.
Azure / AzurePublicDataset
Microsoft Azure Traces
Cyb3r-Monk / Threat-Hunting-and-Detection
Repository for threat hunting and detection queries, etc. for Defender for Endpoint and Microsoft Sentinel in KQL(Kusto Query Language).
leoncuhk / awesome-quant-ai
A curated list of awesome resources for quantitative investment and trading strategies focusing on artificial intelligence and machine learning applications in finance.
AkashSingh3031 / The-Complete-FAANG-Preparation
Dive into this repository, a comprehensive resource covering Data Structures, Algorithms, 450 DSA by Love Babbar, Striver DSA sheet, Apna College DSA Sheet, and FAANG Questions! 🚀 That's not all! We've got Technical Subjects like Operating Systems, DBMS, SQL, Computer Networks, and Object-Oriented Programming, all waiting for you.
oracle-devrel / oracle-ai-developer-hub
Technical resources for AI developers to build applications, agents, and systems using Oracle AI Database and OCI services
microsoft / FLAML
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
apache / hamilton
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.
cksystemsteaching / selfie
An educational software system of a tiny self-compiling C compiler, a tiny self-executing RISC-V emulator, and a tiny self-hosting RISC-V hypervisor.
om-ai-lab / VLX-VR
SDK to use VLX-VR: An Agentic-Aware Video Reasoning Model
evidentlyai / evidently
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.
h2oai / h2o-3
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.
yandexdataschool / Practical_RL
A course in reinforcement learning in the wild