January 2019
Intermediate to advanced
322 pages
7h 29m
English
Content preview from Hands-On Deep Learning with Apache Spark
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Monitoring and Debugging Neural Network Training
The previous chapter focused on training Multilayer Neural Networks (MNNs), and presenting code examples for CNNs and RNNs in particular. This chapter describes how monitoring a network can be done while training is in progress and how to use this monitoring information to tune a model. DL4J provides UI facilities for monitoring and tuning purposes, and will be the centerpiece of this chapter. These facilities also work in a training context with DL4J and Apache Spark. Examples for both situations (training using DL4J only and DL4J with Spark) will be presented. A list of potential baseline steps or tips for network training will also be discussed.
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