Perceptron & Linear Classification
The Foundation of All Neural Networks
What You'll Discover
Journey from complete ignorance to intelligent weather prediction
The Simplest Neural Network
Meet the perceptron - a single neuron that makes binary decisions. It's the building block of every neural network, including ChatGPT!
Decision Boundaries
Watch as the perceptron learns to draw a line that perfectly separates rainy days from sunny days in weather data.
Learning from Mistakes
See how the perceptron adjusts its "opinions" (weights) every time it makes a wrong prediction - just like how you learn!
Real-World Application
Use actual weather data to predict rain based on humidity and temperature - a practical AI application you can understand.
Foundation for Complex AI
Understand how this simple concept scales up to power modern AI systems like image recognition and language models.
Interactive Learning
Step through each prediction, see the math in action, and watch the decision boundary evolve in real-time.
Key Concepts Covered
Linear Classification
Separating data into two categories using a straight line
Decision Boundaries
The line that separates different classes of data
Perceptron Learning Rule
How the algorithm adjusts weights when it makes mistakes
Weight Updates
The mathematical process of learning from errors
Binary Classification
Making yes/no decisions based on input data
Pattern Recognition
How AI systems learn to recognize patterns in data
Ready for More?
Continue your AI journey with these related concepts
🌦️ The Weather Prediction Challenge
Meet Sarah, a weather enthusiast who wants to predict rain using just two simple measurements:
Today's Data: • Humidity: How much moisture is in the air (0-100%) • Temperature: How hot it is outside (0-40°C)
The Question: Can we draw a simple line that separates rainy days from sunny days?
Our Dataset: 10 days of weather history • Rainy Day 1: 72.2% humidity, 17.9°C → 🌧️ RAIN • Rainy Day 2: 77.7% humidity, 16.0°C → 🌧️ RAIN • Rainy Day 3: 81.0% humidity, 15.3°C → 🌧️ RAIN • Rainy Day 4: 62.4% humidity, 20.4°C → 🌧️ RAIN • Rainy Day 5: 62.1% humidity, 22.6°C → 🌧️ RAIN ...and 5 more days!
The Goal: Train the simplest possible "brain" (a perceptron) to learn this pattern. It's like teaching a computer to be a weather forecaster with just one decision rule!
What You'll See: The perceptron architecture shows how inputs (humidity and temperature) flow through weights to make a decision. The scatter plot shows our weather data - notice the pattern? Blue dots (rainy) tend to be in one region, yellow dots (sunny) in another. Can the perceptron learn to draw a line between them?