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Awesome lists & learningpatchy631

ai-engineering-hub

More than 90 projects on LLMs, RAG and agents, sorted by difficulty from beginner to advanced. Each project has its own write-up and code.

Who it is for

For practitioners who want a ladder of tasks from easy to hard.

How to start

  1. Start with ai-engineering-roadmap if you are a beginner
  2. Pick a project from Beginner Projects, such as a simple RAG or OCR app
  3. Move to Intermediate and Advanced projects as you get comfortable

Steps are taken from the README. Check the current version in the repository before running them.

Stars over the last 30 days

+926Sep 6 — Oct 5
37,29238,218

Author's description

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

Shubhamsaboo

awesome-llm-apps

Growing fastest

A large collection of ready-made LLM apps: agents, RAG systems and skills for coding agents. Every template can be run and taken apart piece by piece.

141Kstars+4.8K in 30 dPython

A free 21-lesson Microsoft course that goes from generative AI basics and prompting to working applications. Each lesson ships with code.

121Kstars+2K in 30 dJupyter Notebook

Code for Sebastian Raschka's book: you build a GPT-like model in PyTorch step by step, then pretrain and finetune it. The best way to see how an LLM works inside.

106Kstars+1.8K in 30 dJupyter Notebook

3b1b

manim

An animation engine Grant Sanderson uses to make 3Blue1Brown videos, including the well-known neural network ones. It is not an AI library but a tool for explaining math and ML visually.

95Kstars+1.5K in 30 dPython

A 12-week course on classic machine learning: 26 lessons and 52 quizzes. The foundation that makes modern models easier to understand.

91Kstars+1.2K in 30 dJupyter Notebook

mlabonne

llm-course

A three-part LLM roadmap: fundamentals, the LLM Scientist (building models) and the LLM Engineer (building apps). Topics come with Colab notebooks.

83Kstars+1.1K in 30 d