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RAG for Document Search

Advanced astronaut Difficulty 5/5 Build project Stop 33 / 34 Python ages teen+

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AI-written overview

What is it?

RAG for Document Search is in our AI Model build group, a list of tutorials about building the pieces of an AI system yourself. We only know the title, short description and level from our list.

Is it for me?

It is for people with programming and maths experience. Items are Advanced, so it suits about age teen+ and up and is hard.

Grown-ups: some tutorials need a lot of computer power or a paid service. Check costs before starting.

How to start

  1. Read the description to see what it builds.
  2. Open the tutorial with a grown-up and check what it needs.
  3. Start with the introduction only.

How much time?

Plan about 80 minutes at a time over about 10 sessions. (estimate)

80 min per session 10 sessions estimate

A plan you can follow

  1. Day 1 40 min Read the introduction.
  2. Week 1 90 min Run the first example.
  3. Week 2 90 min Follow the next section.
  4. Week 3 60 min Write down what you understood.

Times are estimates. Go at your own speed.

Go to the learning site

You are about to leave our site to visit RAG for Document Search on another website. We don't control that site. Ask a grown-up before you go. Check the original for details. This site may not be in your language. Your browser can translate the page: look for the translate button near the address bar, or ask a grown-up to help.

You are leaving our site

Grown-ups: this link goes to a site we do not control and have not reviewed beyond its listing. Please look at it first.

Go to the learning site (opens the original site in a new tab)

https://github.com/langchain-ai/rag-from-scratch

On another site. From the list: codecrafters-io/build-your-own-x · License: CC0-1.0 · Build your own AI Model

How to learn from a GitHub project or list

Your path through Python

Stop 31 H2O Resource list Stop 32 Optical Character Recognition (OCR) Build project Stop 33 RAG for Document Search Build project Stop 34 SlowTorch: Implementation of PyTorch from the ground up in 100% pure Python Build project

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