Machine Learning Tutorial: How to Program Without Creating Your Own Algorithms

This tutorial recreates Frank Rosenblatt's 1958 perceptron demonstration, where a machine learning system learned to identify which side of a card contained a shape. The tutorial compares two approaches: a traditional programming method that manually counts pixels versus a perceptron that uses 400 weights to learn patterns from training examples. Through interactive code playback, learners see how the perceptron starts with zero weights and gradually adjusts them based on prediction errors until it successfully identifies card patterns. This example demonstrates the fundamental difference between traditional programming and machine learning, serving as an accessible introduction to neural networks and AI concepts.