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Hands-On Neural Network Programming with C#

You're reading from  Hands-On Neural Network Programming with C#

Product type Book
Published in Sep 2018
Publisher Packt
ISBN-13 9781789612011
Pages 328 pages
Edition 1st Edition
Languages
Author (1):
Matt Cole Matt Cole
Profile icon Matt Cole

Table of Contents (16) Chapters

Preface A Quick Refresher Building Our First Neural Network Together Decision Trees and Random Forests Face and Motion Detection Training CNNs Using ConvNetSharp Training Autoencoders Using RNNSharp Replacing Back Propagation with PSO Function Optimizations: How and Why Finding Optimal Parameters Object Detection with TensorFlowSharp Time Series Prediction and LSTM Using CNTK GRUs Compared to LSTMs, RNNs, and Feedforward networks Activation Function Timings
Function Optimization Reference Other Books You May Enjoy

Creating your own autoencoder

Now that you are an expert on autoencoders, let's move on to less theory and more practice. Let's take a bit of a different route on this one. Instead of using an open-source package and showing you how to use it, let's write our own autoencoder framework that you can enhance to make your own. We'll discuss and implement the basic pieces needed, and then write some sample code showing how to use it. We will make this chapter unique in that we won't finish the usage sample; we'll do just enough to get you started along your own path to autoencoder creation. With that in mind, let's begin.

Let's start off by thinking about what an autoencoder is and what things we would want to include. First off, we're going to need to keep track of the number of layers that we have. These layers will be Restricted Boltzmann...

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