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Deep Learning

Advanced astronaut Difficulty 5/5 Resource list Stop 25 / 42 ages teen+

Neural networks.

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AI-written overview

What is it?

Deep Learning is in our Computer Science group, a list of resources about the ideas behind computing, like how algorithms and data work. We only know the title, short description and level from our list.

Is it for me?

It is for curious people who want to know why computers work, not only how to use them. Many items are Advanced or Intermediate, so it suits about age teen+ and up.

Grown-ups: some material is university level. A hard item is not a problem; just choose an easier one.

How to start

  1. Read the description and see if the idea sounds interesting.
  2. Open the original site with a grown-up and read the first section.
  3. Draw or write the main idea in your own words.

How much time?

Plan about 80 minutes at a time over about 9 sessions. (estimate)

80 min per session 9 sessions estimate

A plan you can follow

  1. Day 1 30 min Read the first section.
  2. Week 1 45 min Take notes and try one example.
  3. Week 2 60 min Explain the idea to someone.
  4. Week 3 60 min Look for the idea in a program you know.

Times are estimates. Go at your own speed.

Go to the learning site

You are about to leave our site to visit Deep Learning 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/ChristosChristofidis/awesome-deep-learning#readme

On another site. From the list: sindresorhus/awesome · License: CC0-1.0 · Computer Science

How to learn from a GitHub project or list

Your path through Math & science

Stop 23 Computer Vision Resource list Stop 24 Core ML Models Resource list Stop 25 Deep Learning Resource list Stop 26 Deep Vision Resource list Stop 27 Empirical Software Engineering Resource list Stop 28 H2O Resource list Stop 29 JAX Resource list

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