January 2019
Intermediate to advanced
322 pages
7h 29m
English
Content preview from Hands-On Deep Learning with Apache Spark
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Image Classification
In the previous chapter, after a quick recap on the concept of convolution, we learned more about the strategies for object recognition and more implementation details through examples in Python (Keras) and Scala (DL4J). This chapter covers the implementation of a full image classification web application or web service. The goal here is to show you how to apply the concepts from the previous chapter to an end-to-end classification system.
The steps to complete this goal are as follows:
- Pick up a proper Keras (with TensorFlow backend) pre-trained CNN model
- Load it and test it in DL4J (and Spark)
- Understand how to retrain the Python model on Apache Spark
- Implement an image classification web application that uses it
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