What is a Neural Network? AI and Deep Learning Explained!

This introduction separates artificial intelligence, machine learning and deep learning. The speaker contrasts conventional programs, where people specify the rules, with machine learning, where a model learns patterns by comparing input data with known outcomes.

A neural network is described as layers of nodes with weights, biases and activation functions. Training repeatedly adjusts those values to reduce error, then tests and validates the result. The video uses a house-pricing example to show how a learned model can make predictions from patterns that are difficult to write as explicit rules.