'Linear separability' presentation slideshows

Support Vector Machines (and Kernel Methods in general)

643 views • 45 slides

Perceptrons Michael J. Watts mike.watts.nz

Perceptrons Michael J. Watts http://mike.watts.net.nz. Lecture Outline. ANN revision Perceptron architecture Perceptron learning Problems with perceptrons. ANN Revision. Artificial neurons mathematical abstractions of biological neurons three functions associated with each neuron input

390 views • 26 slides

Supervised learning network

Supervised learning network. G.Anuradha. Architecture. Earlier attempts to build intelligent and self learning systems using simple components Used to solve simple classification problems Used by Rosenblatt to explain the pattern-recognition abilities of biological visual systems.

466 views • 26 slides

281 views • 20 slides

Backpropagation

Backpropagation. The Plague of Linear Separability. The good news is: Learn-Perceptron is guaranteed to converge to a correct assignment of weights if such an assignment exists The bad news is:

222 views • 20 slides

An Intro to Nerual Networks

261 views • 18 slides

CS 4700: Foundations of Artificial Intelligence

CS 4700: Foundations of Artificial Intelligence. Prof. Carla P. Gomes gomes@cs.cornell.edu Module: Neural Networks Expressiveness of Perceptrons (Reading: Chapter 20.5). Expressiveness of Perceptrons. Expressiveness of Perceptrons. What hypothesis space can a perceptron represent?.

286 views • 18 slides