Skip to Main Content
Advanced Deep Learning with Keras
book

Advanced Deep Learning with Keras

by Rowel Atienza, Neeraj Verma, Valerio Maggio
October 2018
Intermediate to advanced content levelIntermediate to advanced
368 pages
9h 20m
English
Packt Publishing
Content preview from Advanced Deep Learning with Keras

Building autoencoders using Keras

We're now going to move onto something really exciting, building an autoencoder using Keras library. For simplicity, we'll be using the MNIST dataset for the first set of examples. The autoencoder will then generate a latent vector from the input data and recover the input using the decoder. The latent vector in this first example is 16-dim.

Firstly, we're going to implement the autoencoder by building the encoder. Listing 3.2.1 shows the encoder that compresses the MNIST digit into a 16-dim latent vector. The encoder is a stack of two Conv2D. The final stage is a Dense layer with 16 units to generate the latent vector. Figure 3.2.1 shows the architecture model diagram generated by plot_model() which is the same ...

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

Hands-On Neural Networks with Keras

Hands-On Neural Networks with Keras

Niloy Purkait
Deep Learning with Keras

Deep Learning with Keras

Antonio Gulli, Sujit Pal
Keras Deep Learning Cookbook

Keras Deep Learning Cookbook

Rajdeep Dua, Sujit Pal, Manpreet Singh Ghotra

Publisher Resources

ISBN: 9781788629416Supplemental Content