A 21-lesson Microsoft course teaching how to build generative AI applications, with code examples in Python and TypeScript.
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Example notebooks and guides showing how to accomplish common tasks with the OpenAI API.
Open-source large language models and tooling for financial tasks such as sentiment analysis, forecasting, and robo-advisory.
A modular Agentic RAG built with LangGraph β learn Retrieval-Augmented Generation Agents in minutes.
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.
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22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.
A group of notebooks and other files which can help you learn AI from scratch.
End-to-end project training and building AI models / LLMs to detect AI-written text
Everything you need to know to build your own RAG application
Practical course about Large Language Models.
Notebooks & Example Apps for Search, Observability, and Security with Elasticsearch
This repository introduces PIXIU, an open-source resource featuring the first financial large language models (LLMs), instruction tuning data, and evaluation benchmarks to holistically assess financial LLMs. Our goal is to continually push forward the open-source development of financial artificial intelligence (AI).
Learn Python from zero, then understand the AI vocabulary behind ChatGPT and Claude: notebooks, whiteboard notes, assignments and a 21-term AI guide.
[ACL 2024] An Easy-to-use Knowledge Editing Framework for LLMs.
Self-paced bootcamp on Generative AI. Tutorials on ML fundamentals, Ollama, LLMs, RAGs, LangChain, LangGraph, Fine-tuning, DSPy & AI Agents (CrewAI), (Using ChatGPT, gpt-oss, Claude, Qwen, Gemma, Llama, Gemini)