Introduction to Artificial Intelligence - Introduction to Neural Networks - Lecture 20

This lecture from Memorial University's Computer Science 3200/6980 (Winter 2025) introduces neural networks as part of the Artificial Intelligence course taught by Professor David Churchill. Learn about the resurgence of neural networks, biological inspiration from human neurons, and fundamental concepts including Threshold Logic Units, linear separability, and perceptrons. Explore neural network structures, training methodologies, back propagation, and activation functions. Watch a practical demonstration using TensorFlow Playground and discover applications of neural networks in game AI. The lecture also includes updates on Assignment 5 for enrolled students. This is part of a comprehensive introduction to AI covering algorithmic techniques and data structures used in modern problem-solving environments.

Syllabus

00:00 - Intro
00:59 - Neural Nets Resurrected
05:42 - Human Neurons
09:43 - Threshold Logic Units TLU
18:09 - Linear Separability
20:51 - Perceptron Simple Neurons
23:10 - Neural Network Structure
25:39 - Training a Neural Network
27:48 - Back Propagation Brief Overview
34:59 - Activation Function Smoothing
39:29 - Neural Net Structures
43:54 - Neural Net Demo Tensorflow Playground
53:49 - Neural Net Game AI Applications
59:36 - Assignment 5 Updates