Neural Networks - The Nature of Code

Explore neural networks through a comprehensive video series that accompanies Chapter 10 of The Nature of Code book, covering fundamental concepts from basic perceptrons to advanced backpropagation algorithms. Begin with an introduction to neural networks and progress through building single-layer perceptrons before advancing to multilayer perceptrons and essential matrix mathematics for neural network computations. Master the implementation of feedforward algorithms and dive deep into backpropagation techniques across multiple detailed sessions. Learn to update your code to modern ES6 standards while improving matrix class functionality for better performance. Apply your knowledge through practical coding challenges including solving the XOR problem and creating a neural network color predictor. Extend your learning with a complete doodle classifier project that demonstrates data preparation in both Processing and p5.js, model training, testing procedures, and real-time classification of user-generated drawings. Gain hands-on experience with both theoretical foundations and practical implementations of neural networks through 8 hours and 48 minutes of detailed instruction from the Coding Train.

Syllabus

10.1: Introduction to Neural Networks - The Nature of Code
10.2: Neural Networks: Perceptron Part 1 - The Nature of Code
10.3: Neural Networks: Perceptron Part 2 - The Nature of Code
10.4: Neural Networks: Multilayer Perceptron Part 1 - The Nature of Code
10.5: Neural Networks: Multilayer Perceptron Part 2 - The Nature of Code
10.6: Neural Networks: Matrix Math Part 1 - The Nature of Code
10.7: Neural Networks: Matrix Math Part 2 - The Nature of Code
10.8: Neural Networks: Updating Code to ES6 - The Nature of Code
10.9: Neural Networks: Matrix Math Part 3 - The Nature of Code
10.10: Neural Networks: Matrix Math Part 4 - The Nature of Code
10.11: Neural Networks: Matrix Class Improvements - The Nature of Code
10.12: Neural Networks: Feedforward Algorithm Part 1 - The Nature of Code
10.13: Neural Networks: Feedforward Algorithm Part 2 - The Nature of Code
10.14: Neural Networks: Backpropagation Part 1 - The Nature of Code
10.15: Neural Networks: Backpropagation Part 2 - The Nature of Code
10.16: Neural Networks: Backpropagation Part 3 - The Nature of Code
10.17: Neural Networks: Backpropagation Part 4 - The Nature of Code
10.18: Neural Networks: Backpropagation Part 5 - The Nature of Code
Coding Challenge #92: XOR Problem
Coding Challenge #99: Neural Network Color Predictor
5.1: Doodle Classifier: Introduction - Intelligence and Learning
5.2: Doodle Classifier: Prepping Data in Processing - Intelligence and Learning
5.3: Doodle Classifier: Prepping Data in p5.js - Intelligence and Learning
5.4: Doodle Classifier: Training - Intelligence and Learning
5.5: Doodle Classifier: Testing - Intelligence and Learning
5.6: Doodle Classifier: Classifying User Data - Intelligence and Learning