Understanding AI from Scratch – Neuaral Networks Without Libraries Course

Learn the fundamentals of Neural Networks by building one from scratch without libraries. You'll manually tweak network parameters to teach a car how to drive within a specially crafted playground. Dr. Radu teaches computer science at a university in Finland, and has over a decade of experience with machine learning and AI, and he emphasizes the importance of revisiting basics in an era of easy-to-use complex models.

You will have homework assignments which you can discuss with Dr. Radu on his Discord: discord.gg/gJFcF5XVn9

✏️ Course developed by @Radu

🏆 Win prizes by following along:    • ⭐🏆⭐PRIZES: Racing AI Competition⭐🏆⭐ D...  

🚗 THE PLAYGROUND: https://radufromfinland.com/projects/...

🚙 HELP COLLECT DATA BY RACING: https://radufromfinland.com/projects/...

⭐ OTHER LINKS ⭐
Phase 1 – Self-Driving Car with JavaScript:    • Self-Driving Car with JavaScript Cour...  
Phase 2 – Virtual World Filled with Self-Driving Cars:    • Build a Virtual World Filled with Sel...  

Vanilla JavaScript Chart Tutorial:    • Build a Chart using JavaScript (No Li...  
Machine Learning JavaScript Course:    • No Black Box Machine Learning Course ...  

3b1b's Neural Network Video:    • But what is a neural network? | Chapt...  
Another Playground: https://playground.tensorflow.org
Desmos 3D: https://www.desmos.com/3d
Another Playground: https://playground.tensorflow.org
Top-view Cars Clip:    • BEST TOP VIEW ROAD TRAFFIC CAR VIDEO ...  


💻 CODE 💻
1. Phase 1 https://github.com/gniziemazity/self-...
2. Phase 2 https://github.com/gniziemazity/virtu...
3. Phase 3 https://github.com/gniziemazity/under...
💻 Use "11. MiniMap" from Phase 2 at 02:36:49
💻 Use "1. Starting Codebase" from Phase 3 in Lesson 6 (if you didn't code anything yet)

☕ Buy Radu a Coffee: https://www.buymeacoffee.com/radum

⚡️Join Radu's Channel:    / @radu  

⭐ Contents ⭐
⌨️ (0:00:00) Introduction
⌨️ (0:07:12) The Playground
⌨️ (0:14:34) One Neuron
⌨️ (0:29:07) Clarrifications
⌨️ (0:31:58) Lesson 2
⌨️ (0:32:16) Genetic Algorithm
⌨️ (0:43:04) 2 Inputs
⌨️ (1:02:42) Hidden Layers
⌨️ (1:13:03) Misconceptions
⌨️ (1:14:18) Lesson 3 (More Outputs)
⌨️ (1:55:59) Lesson 4 (Traffic Rules)
⌨️ (2:24:10) Lesson 5 (Compass Sensor)
⌨️ (2:35:20) The need for Shortest Path
⌨️ (2:37:10) Updating the Self-driving Car codebase
⌨️ (2:57:39) Lesson 6 (Dijkstra's Algorithm)
⌨️ (3:24:03) Lesson 7 (Dijkstra with AI Agents)
⌨️ (3:43:13) Final Challenge