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

Democratizing Reinforcement Learning for LLMs

Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.

Witness the aha moment of VLM with less than $3.

ZenML 🙏: The bridge between ML and Ops. https://zenml.io.

Attention is all you need implementation

A course on aligning smol models.

🙌 OpenHands: Code Less, Make More

Notes from the Latent Space paper club. Follow along or start your own!

This repo has the code of the 3 demos I presented at Google Gemma2 DevDay Tokyo, using Gemma2 on a Jetson Orin Nano device.

The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, No-code agent builder, and more.

Build Multimodal AI Agents with memory, knowledge and tools. Simple, fast and model-agnostic.

[ICLR 2023] ReAct: Synergizing Reasoning and Acting in Language Models

Langflow is a low-code app builder for RAG and multi-agent AI applications. It’s Python-based and agnostic to any model, API, or database.

Examples and guides for using the Gemini API

Finetune Llama 3.3, DeepSeek-R1 & Reasoning LLMs 2x faster with 70% less memory! 🦥

Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI

https://huyenchip.com/ml-interviews-book/

Curated list of data science interview questions and answers

Distributed Asynchronous Hyperparameter Optimization in Python

Gurobi modeling examples

A curated list of Large Language Model resources, covering model training, serving, fine-tuning, and building LLM applications.

This repository contains demos I made with the Transformers library by HuggingFace.

Fast, Flexible and Portable Structured Generation

Simple, unified interface to multiple Generative AI providers

Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.

This is a repo with links to everything you'd ever want to learn about data engineering

🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 12 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴