Understanding AI from Scratch – Neuaral Networks Without Libraries Course

Curriculum for the course Understanding AI from Scratch – Neuaral Networks Without Libraries Course

Understanding AI from Scratch – Neuaral Networks Without Libraries Course Learn the fundamentals of Neural Networks by building one from scatch without libraries. You'll manually tweak network parameters to teach a car how to drive within a specially crafted playground. Dr. Radu 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 Radu on his Discord: discord.gg/gJFcF5XVn9 ✏️ Course developed by @Radu 🏆 Win prizes by following along: https://youtu.be/EhJ7qD5HwpY 🚗 THE PLAYGROUND: https://radufromfinland.com/projects/aiCarPlayground/?s=default 🚙 HELP COLLECT DATA BY RACING: https://radufromfinland.com/projects/aiRacer ⭐ OTHER LINKS ⭐ Phase 1 – Self-Driving Car with JavaScript: https://youtu.be/Rs_rAxEsAvI Phase 2 – Virtual World Filled with Self-Driving Cars: https://youtu.be/5iHejdqYIa8 Vanilla JavaScript Chart Tutorial: https://youtu.be/n8uCt1TSGKE Machine Learning JavaScript Course: https://youtu.be/vDDjtwQDw2k 3b1b's Neural Network Video: https://youtu.be/aircAruvnKk?si=JB6fvUT3Ko1mkU3x Another Playground: https://playground.tensorflow.org Desmos 3D: https://www.desmos.com/3d Another Playground: https://playground.tensorflow.org Top-view Cars Clip: https://youtu.be/jZrjE_ixu18 💻 CODE 💻 1. Phase 1 https://github.com/gniziemazity/self-driving-car 2. Phase 2 https://github.com/gniziemazity/virtual-world 3. Phase 3 https://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: https://www.buymeacoffee.com/radum ⭐ 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

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