Book Image

Hands-On Deep Learning with Apache Spark

By : Guglielmo Iozzia
Book Image

Hands-On Deep Learning with Apache Spark

By: Guglielmo Iozzia

Overview of this book

Deep learning is a subset of machine learning where datasets with several layers of complexity can be processed. Hands-On Deep Learning with Apache Spark addresses the sheer complexity of technical and analytical parts and the speed at which deep learning solutions can be implemented on Apache Spark. The book starts with the fundamentals of Apache Spark and deep learning. You will set up Spark for deep learning, learn principles of distributed modeling, and understand different types of neural nets. You will then implement deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) on Spark. As you progress through the book, you will gain hands-on experience of what it takes to understand the complex datasets you are dealing with. During the course of this book, you will use popular deep learning frameworks, such as TensorFlow, Deeplearning4j, and Keras to train your distributed models. By the end of this book, you'll have gained experience with the implementation of your models on a variety of use cases.
Table of Contents (19 chapters)
Appendix A: Functional Programming in Scala
Appendix B: Image Data Preparation for Spark

Alternatives to DL4J for the Scala programming language

DL4J isn't the only framework for deep learning available for the Scala programming language. Two open source alternatives exist. In this section, we are going to learn more about them and do a comparison with DL4J.

BigDL

BigDL (https://bigdl-project.github.io/0.6.0/) is an open source, distributed, deep learning framework for Apache Spark implemented by Intel (https://www.intel.com). It is licensed with the Apache 2.0 license, the same as for DL4J. It has been implemented in Scala and exposes APIs for Scala and Python. It doesn't provide support for CUDA. While DL4J allows cross-platform execution in standalone mode (including Android mobile devices) and distributed...