Machine Learning ยท Lesson 9
Neural Networks: From Neurons to Learning
Explore neurons, weights, activation functions, layers, forward propagation, loss, and gradient-based learning through interactive labs and business examples.
What is a neural network?
A model made of connected computational units that learns patterns.
A neural network is a machine learning model built from connected units often called neurons. Each unit receives numerical inputs, combines them using learned parameters, and passes a result forward. During training, the network adjusts its parameters to reduce prediction error. Neural networks can learn complex relationships, but they still depend on suitable data, evaluation, and problem design.
Business meaning
A bank might use a neural network to combine transaction amount, account age, and purchase context to estimate whether a transaction is suspicious.
Select a stage to see its role. This is a conceptual diagram, not a trained network.
Try it
Inspect the network diagram above. What does a neural network learn during training?
Quick knowledge check
Which description best fits a neural network?