Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Hands-On Neural Network Programming with C#

You're reading from   Hands-On Neural Network Programming with C# Add powerful neural network capabilities to your C# enterprise applications

Arrow left icon
Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781789612011
Length 328 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Matt Cole Matt Cole
Author Profile Icon Matt Cole
Matt Cole
Arrow right icon
View More author details
Toc

Table of Contents (16) Chapters Close

Preface 1. A Quick Refresher FREE CHAPTER 2. Building Our First Neural Network Together 3. Decision Trees and Random Forests 4. Face and Motion Detection 5. Training CNNs Using ConvNetSharp 6. Training Autoencoders Using RNNSharp 7. Replacing Back Propagation with PSO 8. Function Optimizations: How and Why 9. Finding Optimal Parameters 10. Object Detection with TensorFlowSharp 11. Time Series Prediction and LSTM Using CNTK 12. GRUs Compared to LSTMs, RNNs, and Feedforward networks 13. Activation Function Timings
14. Function Optimization Reference 15. Other Books You May Enjoy

Creating a network

Using the ConvNetSharp framework, there are three ways in which to create a neural network. First, we can use the Core.Layers or Flow.Layers objects to create a convolutional network (with or without a computational graph), as shown in the following diagram:

Alternatively, we can create a computational graph like the following:

Example 1 – a simple example

Let's take a look at our first example. This is a minimal example in which we will define a two-layer neural network and train it on a single data point. We are intentionally making this example verbose so that we can walk through each step together to improve our understanding:

var net = new Net<double>();

The InputLayer variable declares...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image