All repos — GH Trending Explorer

rasbt / LLMs-from-scratch

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

mrdbourke / zero-to-mastery-ml

Course materials, code, notebooks and datasets for the Zero to Mastery Machine Learning and Data Science course.

learning-resources ml-framework data-science

UFund-Me / Qbot

Open-source AI-oriented quantitative investment platform covering data, strategy research, backtesting, simulated and live trading.

ml-framework data-science quantitative-finance

NirDiamant / RAG_Techniques

A collection of 42+ runnable Jupyter notebooks, each tutorial covering an advanced technique for Retrieval-Augmented Generation systems.

llm-tooling learning-resources semantic-search

google-research / google-research

Monorepo of research code and datasets released by Google Research, spanning many subprojects.

ml-framework science

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.

learning-resources education ml-framework

patchy631 / ai-engineering-hub

In-depth tutorials on LLMs, RAGs and real-world AI agent applications.

alirezadir / AIMLInterviews

A study guide and interview-prep curriculum for AI/ML technical roles at big tech, covering coding, ML breadth, system design, and behavioral rounds.

learning-resources ai-agents mcp

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.

learning-resources education ml-framework

NirDiamant / GenAI_Agents

50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.

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】

stefan-jansen / machine-learning-for-trading

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

DataTalksClub / mlops-zoomcamp

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

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.

learning-resources ml-framework backend

higgsfield-ai / higgsfield

Open-source GPU cluster orchestrator and PyTorch-based framework for training LLMs with billions to trillions of parameters.

ml-framework devops cluster-management

rasbt / reasoning-from-scratch

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

fastai / fastbook

The fastai book, published as Jupyter Notebooks

AI4Finance-Foundation / FinGPT

FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.

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.

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.

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.

NVlabs / sionna

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

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.

microsoft / FLAML

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

girafe-ai / ml-course

Open Machine Learning course

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

openvinotoolkit / openvino_notebooks

📚 Jupyter notebook tutorials for OpenVINO™

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.

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.

numerai / example-scripts

A collection of scripts and notebooks to help you get started quickly.

joanby / python-ml-course

Curso de Introducción a Machine Learning con Python

petrobras / 3W

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

fastai / fastai

The fastai deep learning library

shap / shap

A game theoretic approach to explain the output of any machine learning model.

aws / amazon-sagemaker-examples

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

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.

tensorflow / docs

TensorFlow documentation

skorch-dev / skorch

A scikit-learn compatible neural network library that wraps PyTorch

dusty-nv / jetson-containers

Machine Learning Containers for NVIDIA Jetson and JetPack-L4T

makcedward / nlpaug

Data augmentation for NLP

tensorflow / probability

Probabilistic reasoning and statistical analysis in TensorFlow

bragai / bRAG-langchain

Everything you need to know to build your own RAG application

hemansnation / AI-Engineer-Headquarters

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

ben1234560 / AiLearning-Theory-Applying

快速上手AI理论及应用实战：基础知识、Transformer、NLP、ML、DL、竞赛。含大量注释及数据集，力求每一位能看懂并复现。

MAIF / shapash

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

scikit-learn-contrib / hdbscan

A high performance implementation of HDBSCAN clustering.

x4nth055 / pythoncode-tutorials

The Python Code Tutorials

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.