Stars
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
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.
Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. The next cohort starts in January 2026. Join the course here 👇🏼
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
Official code repo for the O'Reilly Book - "Hands-On Large Language Models"
This repository provides tutorials and implementations for various Generative AI Agent techniques, from basic to advanced. It serves as a comprehensive guide for building intelligent, interactive A…
Code for Machine Learning for Algorithmic Trading, 2nd edition.
This repository delivers end-to-end, code-first tutorials covering every layer of production-grade GenAI agents, guiding you from spark to scale with proven patterns and reusable blueprints for re…
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Learn ML engineering for free in 4 months! Register here 👇🏼
Python training for business analysts and traders
Python toolkit for quantitative finance
100+ Fine-tuning Tutorial Notebooks on Google Colab, Kaggle and more.
Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.
Automatic Generation of Visualizations and Infographics using Large Language Models
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.
Machine Learning in Finance: From Theory to Practice Book
About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008
Documentation for Google's Gen AI site - including the Gemini API and Gemma
Code and Slides
PyMC educational resources
Samples using the Agent2Agent (A2A) Protocol