rasbt / LLMs-from-scratch

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

stefan-jansen / machine-learning-for-trading

Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.

xiaolai / the-craft-of-selfteaching

One has no future if one couldn't teach themself.

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】

DataTalksClub / mlops-zoomcamp

Free MLOps course from DataTalks.Club. Register here 👇🏼 to get notified about the next cohort

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.

scikit-learn-contrib / MAPIE

A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.

Lifelong-Robot-Learning / LIBERO

Benchmarking Knowledge Transfer in Lifelong Robot Learning

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。

DataTalksClub / llm-zoomcamp

LLM Zoomcamp - a free online course about real-life applications of LLMs. In 10 weeks you will learn how to build an AI system that answers questions about your knowledge base. Register here 👇🏼

Visualize-ML / Linear-Algebra-Made-Easy---Learn-with-Python-and-Visualization

”数学不难“ 之 《线性代数不难》上下册，66话题完册；欢迎批评指正

mrdbourke / pytorch-deep-learning

Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.

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.

rasbt / reasoning-from-scratch

Implement a reasoning LLM in PyTorch from scratch, step by step

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.

NVDLI / fundamentals-of-deep-learning

DLI Fundamentals of Deep Learning

facebookresearch / dinov2

PyTorch code and models for the DINOv2 self-supervised learning method.

GiovanniPasq / agentic-rag-for-dummies

A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.

shahidazam2020-oss / A-Comparative-Machine-Learning-Framework-for-Heart-Attack-Risk-Prediction-Using-Data-Preprocessing

This project presents a comparative machine learning framework for heart attack risk prediction using Python. It includes data preprocessing, feature engineering, SMOTE for class balancing, cross validation, and performance evaluation of multiple ML models.

leandromoreira / digital_video_introduction

A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding). Translations: 🇺🇸 🇨🇳 🇯🇵 🇮🇹 🇰🇷 🇷🇺 🇧🇷 🇪🇸

alphacep / vosk-api

Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node

onnx / models

A collection of pre-trained, state-of-the-art models in the ONNX format

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.

loveunk / deep-learning-llm-agent-notes

机器学习、深度学习的学习路径及知识总结

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.

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/

Akun-python / autumn-recruitment

Autumn-Recruit Algo Notes(秋招算法学习仓库)，面向大模型时代的算法、工程与AI学习共建仓库。从数学基础、数据结构，到机器学习、深度学习、LLM、Agent、AI-Infra、语音与数据科学，通过「理解→推导→手写 → 运行 → 验证 → 复盘构建可持续迭代的知识体系。

fastai / fastbook

The fastai book, published as Jupyter Notebooks

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.

NVlabs / sionna

Sionna: An Open-Source Library for Research on Communication Systems

hemansnation / AI-Engineer-Headquarters

A collection of scientific methods, processes, algorithms, and systems to build stories & models.

Denys88 / rl_games

RL implementations

AlibabaCloudDocs / aliyun_acp_learning

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langchain-ai / langgraph-101

Learn about the fundamentals of LangGraph through a series of notebooks

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.

NirDiamant / Prompt_Engineering

22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.

huggingface / setfit

Efficient few-shot learning with Sentence Transformers

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.

luisguiserrano / manning

Repository for the book Grokking Machine Learning, by Manning Editors

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.

alexeygrigorev / mlbookcamp-code

The code from the Machine Learning Bookcamp book

spmallick / learnopencv

Learn OpenCV : C++ and Python Examples

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.

microsoft / FLAML

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

MAIF / shapash

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

openvinotoolkit / openvino_notebooks

📚 Jupyter notebook tutorials for OpenVINO™

Ramakm / AI-Engineering

A group of notebooks and other files which can help you learn AI from scratch.

intro-stat-learning / ISLP_labs

Up-to-date version of labs for ISLP

simpler-env / SimplerEnv

Evaluating and reproducing real-world robot manipulation policies (e.g., RT-1, RT-1-X, Octo) in simulation under common setups (e.g., Google Robot, WidowX+Bridge) (CoRL 2024)

petrobras / 3W

Timely detections for more proactive and effective actions in offshore oil wells!

rasbt / deeplearning-models

A collection of various deep learning architectures, models, and tips

roboflow / notebooks

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.

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.

tensorflow / probability

Probabilistic reasoning and statistical analysis in TensorFlow

Nixtla / nixtla

TimeGPT-2.1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.

girafe-ai / ml-course

Open Machine Learning course

facebookresearch / Pearl

A Production-ready Reinforcement Learning AI Agent Library brought by the Applied Reinforcement Learning team at Meta.

Tanu-N-Prabhu / Python

This repository helps you learn Python and Machine Learning from scratch.

epfml / ML_course

EPFL Machine Learning Course, Fall 2026

stanfordmlgroup / ngboost

Natural Gradient Boosting for Probabilistic Prediction