April 2017
Intermediate to advanced
318 pages
7h 40m
English
In this chapter, we covered some deep learning networks that were not covered in earlier chapters. We started with a brief look into the Keras functional API, which allows us to build networks that are more complex than the sequential networks we have seen so far. We then looked at regression networks, which allow us to do predictions in a continuous space, and opens up a whole new range of problems we can solve. However, a regression network is really a very simple modification of a standard classification network. The next area we looked at was autoencoders, which are a style of network that allows us to do unsupervised learning and make use of the massive amount of unlabeled data that all of us have access to nowadays. We also ...