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Hands-On Deep Learning with Apache Spark: Build and deploy distributed deep learning applications on Apache Spark

By: Guglielmo Iozzia

Speed up the design and implementation of deep learning solutions using Apache Spark

Key Features

  • Explore the world of distributed deep learning with Apache Spark
  • Train neural networks with deep learning libraries such as BigDL and TensorFlow
  • Develop Spark deep learning applications to intelligently handle large and complex datasets

Book Description

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 impl

Product Details

  • Pages:322 pages
  • Publication Date:Thu Jan 31 2019
  • Publisher:Packt Publishing; 1 edition
  • Language:English
  • Readers:34

Product Description

Speed up the design and implementation of deep learning solutions using Apache Spark

Key Features

  • Explore the world of distributed deep learning with Apache Spark
  • Train neural networks with deep learning libraries such as BigDL and TensorFlow
  • Develop Spark deep learning applications to intelligently handle large and complex datasets

Book Description

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.

What you will learn

  • Understand the basics of deep learning
  • Set up Apache Spark for deep learning
  • Understand the principles of distribution modeling and different types of neural networks
  • Obtain an understanding of deep learning algorithms
  • Discover textual analysis and deep learning with Spark
  • Use popular deep learning frameworks, such as Deeplearning4j, TensorFlow, and Keras
  • Explore popular deep learning algorithms

Who this book is for

If you are a Scala developer, data scientist, or data analyst who wants to learn how to use Spark for implementing efficient deep learning models, Hands-On Deep Learning with Apache Spark is for you. Knowledge of the core machine learning concepts and some exposure to Spark will be helpful.

Table of Contents

  1. The Apache Spark Ecosystem
  2. Deep Learning Basics
  3. Extract, Transform, Load
  4. Streaming
  5. Convolutional Neural Networks
  6. Recurrent Neural Networks
  7. Training Neural Networks with Spark
  8. Monitoring and Debugging Neural Network Training
  9. Interpreting Neural Network Output
  10. Deploying on a Distributed System
  11. NLP Basics
  12. Textual Analysis and Deep Learning
  13. Convolution
  14. Image Classification
  15. What’s Next for Deep Learning?