patchy631 / ai-engineering-hub
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
patchy631 / ai-engineering-hub
Lordog / dive-into-llms
《动手学大模型Dive into LLMs》系列编程实践教程
microsoft / generative-ai-for-beginners
21 Lessons, Get Started Building with Generative AI
datawhalechina / diy-llm
Covers pre-training data, Tokenizer, Transformer, MoE,distributed training, Scaling Laws, inference & alignment .6 progressive code assignments for full-stack LLM learning | 涵盖预训练数据、分词器、Transformer、MoE、分布式训练、缩放定律、推理与对齐，6 项渐进代码作业，掌握 LLM 全栈知识
rasbt / LLMs-from-scratch
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
karpathy / nn-zero-to-hero
Neural Networks: Zero to Hero
xiaolai / the-craft-of-selfteaching
One has no future if one couldn't teach themself.
microsoft / ML-For-Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
DataTalksClub / data-engineering-zoomcamp
Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. Join the course here 👇🏼
anthropics / prompt-eng-interactive-tutorial
Anthropic's Interactive Prompt Engineering Tutorial
microsoft / Data-Science-For-Beginners
10 Weeks, 20 Lessons, Data Science for All!
GokuMohandas / Made-With-ML
Learn how to develop, deploy and iterate on production-grade ML applications.
gepa-ai / gepa
Optimize prompts, code, and more with AI-powered Reflective Optimization
Barry81-666 / kaggle-portfolio
Curated Kaggle projects in computational biology, medical imaging, data science and machine learning.
AccumulateMore / CV
✅（已完结）超级全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】【大飞 大模型Agent】
chiphuyen / aie-book
[WIP] Resources for AI engineers. Also contains supporting materials for the book AI Engineering (Chip Huyen, 2025)
microsoft / mcp-for-beginners
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.
google-research / google-research
Google Research
hugo2046 / QuantsPlaybook
量化研究-券商金工研报复现
NVIDIA / accelerated-computing-hub
NVIDIA curated collection of educational resources related to general purpose GPU programming.
facebookresearch / audiocraft
Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable music generation LM with textual and melodic conditioning.
AI4Finance-Foundation / FinGPT
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
facebookresearch / dinov3
Reference PyTorch implementation and models for DINOv3
NirDiamant / agents-towards-production
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
alirezadir / AIMLInterviews
A Comprehensive Guide for Generative AI, Agentic AI, Multimodal AI, Physical AI Interviews. Proven Formula for multiple FAANG offers and more
pyannote / pyannote-audio
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
facebookresearch / sam2
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
facebookresearch / segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
greyhatguy007 / Machine-Learning-Specialization-Coursera
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
P90-RushB / robopaint-bench
A robot-painting benchmark for multimodal language models: reference images, text prompts, and custom goals. Built on AgentArk.
Exorust / TorchLeet
LeetCode for PyTorch — 65 ML/AI interview problems from real interviews at Google, Meta, Anthropic. Jupyter notebooks, an auto-grader, and an MCP AI tutor.
calmrocks / ai-engineer-notebooks
Hands-on, framework-free Colab notebooks for the AI Engineer / Forward Deployed Engineer (FDE) skill set — model APIs, structured output, tool calling, RAG, evals-as-the-spine, agents (loop from scratch, tool design, guardrails, MCP, Skills), fine-tuning vs LoRA, prompt-injection/security, LLMOps, and customer craft. Runs on the free Groq API.
CompVis / stable-diffusion
A latent text-to-image diffusion model
duoan / TorchCode
🔥 LeetCode for PyTorch — practice implementing softmax, attention, GPT-2 and more from scratch with instant auto-grading. Jupyter-based, self-hosted or try online.
mahmoud / awesome-python-applications
💿 Free software that works great, and also happens to be open-source Python.
raiyanyahya / how-to-train-your-gpt
Build a modern LLM from scratch. Every line commented. Explained like we are five.
cantaro86 / Financial-Models-Numerical-Methods
Collection of notebooks about quantitative finance, with interactive python code.
scikit-learn-contrib / MAPIE
A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.
shap / shap
A game theoretic approach to explain the output of any machine learning model.
norvig / pytudes
Python programs, usually short, of considerable difficulty, to perfect particular skills.
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.
shsarv / Machine-Learning-Projects
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.
yandexdataschool / nlp_course
YSDA course in Natural Language Processing
ProsusAI / finBERT
Financial Sentiment Analysis with BERT
NirDiamant / Prompt_Engineering
22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.
genieincodebottle / generative-ai
Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.
alibaba / clusterdata
cluster data collected from production clusters in Alibaba for cluster management research
NVlabs / sionna
Sionna: An Open-Source Library for Research on Communication Systems
AllenDowney / ThinkDSP
Think DSP: Digital Signal Processing in Python, by Allen B. Downey.
probml / pyprobml
Python code for "Probabilistic Machine learning" book by Kevin Murphy
sokrypton / ColabFold
Making Protein folding accessible to all!
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.
peterdsharpe / AeroSandbox
Aircraft design optimization made fast through computational graph transformations (e.g., automatic differentiation). Composable analysis tools for aerodynamics, propulsion, structures, trajectory design, and much more.
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.
NVIDIA / torch-harmonics
Differentiable signal processing on the sphere for PyTorch
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.
girafe-ai / ml-course
Open Machine Learning course
MARKTECHPOST-AI-MEDIA-INC / AI-Agents-Projects-Tutorials
Multi-agent systems, memory, planning, reasoning loops
stanfordmlgroup / ngboost
Natural Gradient Boosting for Probabilistic Prediction