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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: kzbin.info/www/bejne/e5mtaKR6aq2qprs
🚗 THE PLAYGROUND: radufromfinland.com/projects/aiCarPlayground/?s=default
🚙 HELP COLLECT DATA BY RACING: radufromfinland.com/projects/aiRacer
⭐ OTHER LINKS ⭐
Phase 1 - Self-Driving Car with JavaScript: kzbin.info/www/bejne/iKTCo3Sueth0rKs
Phase 2 - Virtual World Filled with Self-Driving Cars: kzbin.info/www/bejne/a5qrlp2apr58l5o
Vanilla JavaScript Chart Tutorial: kzbin.info/www/bejne/pGnYdKdnibh6gac
Machine Learning JavaScript Course: kzbin.info/www/bejne/rHWnm6ethqmqaM0
3b1b's Neural Network Video: kzbin.info/www/bejne/l5rVlHSoqtuhgc0si=JB6fvUT3Ko1mkU3x
Another Playground: playground.tensorflow.org
Desmos 3D: www.desmos.com/3d
Another Playground: playground.tensorflow.org
Top-view Cars Clip: kzbin.info/www/bejne/oIvVm3iVnt2oZ5o
💻 CODE 💻
1. Phase 1 github.com/gniziemazity/self-driving-car
2. Phase 2 github.com/gniziemazity/virtual-world
3. Phase 3 github.com/gniziemazity/understanding_ai
💻 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: www.buymeacoffee.com/radum
⚡️Join Radu's Channel: youtube.com/@radu/join
⭐ 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