Neural Networks, Visually Explained (3Blue1Brown)

About this course

Grant Sanderson's beautifully animated chapters on how neural networks learn and how large language models work, with no code required. Who it's for: anyone curious about AI, from school students to professionals. These are the free, official videos of the "Neural networks" playlist from the 3Blue1Brown YouTube channel (youtube.com/@3blue1brown). All videos belong to 3Blue1Brown; Sikhami is not affiliated with 3Blue1Brown and simply arranges the public playlist into a course, so you can learn one lesson at a time and keep track of your progress.

What you will learn

• What a neural network is • Gradient descent: how networks learn • Backpropagation, intuitively and with calculus • Large language models explained briefly • Transformers and attention, step by step • How LLMs might store facts, and how AI image and video models work

Course content

1 section · 10 lectures · 3h 37m

1. 1. Neural networks

   • But what is a neural network? | Deep learning chapter 118m
   • Gradient descent, how neural networks learn | Deep Learning Chapter 220m
   • Backpropagation, intuitively | Deep Learning Chapter 312m
   • Backpropagation calculus | Deep Learning Chapter 410m
   • Large Language Models explained briefly7m
   • Transformers, the tech behind LLMs | Deep Learning Chapter 527m
   • Attention in transformers, step-by-step | Deep Learning Chapter 626m
   • How might LLMs store facts | Deep Learning Chapter 722m
   • But what is cross-entropy? | Compression is Intelligence Part 233m
   • But how do AI images and videos actually work? | Guest video by Welch Labs37m