Introduction to the Perceptron Algorithm

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (29)

Page 3 of 3

Support Vector Machines: Linear Separability

Explores linear separability in support vector machines, focusing on hyperplane separation and margin optimization.

Symmetry in Modern Space

Explores the fundamental theorem of isometries in space and the modern definition of symmetry, emphasizing the complexities of determining symmetries in 3D objects.

Product of 4 Plane Reflections: Normalization

Explores the normalization of the product of 4 plane reflections in space.

Neural Networks: Perceptron Model and Backpropagation Algorithm

Covers the perceptron model and backpropagation algorithm in neural networks.

Symmetry in Modern Space

Explores the classification and practical applications of symmetries in 3D space, emphasizing user-driven determination of object symmetries.

Special Cases of 3 Plane Reflections

Explores the configurations and transformations of three planes in space.

Introduction to Learning by Stochastic Gradient Descent: Simple Perceptron

Covers the derivation of the stochastic gradient descent formula for a simple perceptron and explores the geometric interpretation of classification.

3 Reflection Planes Normalization

Explores the normalization of three reflection planes in geometry through rotor-reflections and glided reflections.

Isometries in Space: Orientation & Reflections

Explores isometries in space, transformations preserving lengths and angles, including reflections, rotations, and translations.