Skip to Main Content
Practical Neural Network Recipies in C++
book

Practical Neural Network Recipies in C++

by Masters
June 2014
Intermediate to advanced content levelIntermediate to advanced
493 pages
20h 30m
English
Morgan Kaufmann
Content preview from Practical Neural Network Recipies in C++
Contents
Preface χνϋ
1.
Foundations 1
Motivation 2
New Life for Old Techniques 3
Perceptrons and Linear Separability 4
Neural Network Capabilities 6
Basic Structure of a Neural Network 8
Training 9
Validation 10
Leave-/r-out Method 12
2.
Classification 15
Binary Decisions 16
Making the Decision 17
Multiple Classes 18
Reject Category 18
Making the Decision 19
Other Encoding Schemes 19
Supervised versus Unsupervised Training 21
3.
Autoassociation 23
Autoassociative Filtering 24
Code for Autoassociative Filtering 28
Noise Reduction 29
Learning a Prototype from Exemplars 31
Exposing Isolated Events 32
Pattern Completion 40
Error Correction 41
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Neural Networks with Keras Cookbook

Neural Networks with Keras Cookbook

V Kishore Ayyadevara
Scientific Computing with Python 3

Scientific Computing with Python 3

Claus Führer, Claus Fuhrer, Jan Erik Solem, Olivier Verdier
Mastering Java Machine Learning

Mastering Java Machine Learning

Uday Kamath, Krishna Choppella

Publisher Resources

ISBN: 9780080514338