Book Image

Mastering Apache Spark 2.x - Second Edition

Book Image

Mastering Apache Spark 2.x - Second Edition

Overview of this book

Apache Spark is an in-memory, cluster-based Big Data processing system that provides a wide range of functionalities such as graph processing, machine learning, stream processing, and more. This book will take your knowledge of Apache Spark to the next level by teaching you how to expand Spark’s functionality and build your data flows and machine/deep learning programs on top of the platform. The book starts with a quick overview of the Apache Spark ecosystem, and introduces you to the new features and capabilities in Apache Spark 2.x. You will then work with the different modules in Apache Spark such as interactive querying with Spark SQL, using DataFrames and DataSets effectively, streaming analytics with Spark Streaming, and performing machine learning and deep learning on Spark using MLlib and external tools such as H20 and Deeplearning4j. The book also contains chapters on efficient graph processing, memory management and using Apache Spark on the cloud. By the end of this book, you will have all the necessary information to master Apache Spark, and use it efficiently for Big Data processing and analytics.
Table of Contents (21 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
10
Deep Learning on Apache Spark with DeepLearning4j and H2O

Artificial neural networks


The following figure shows a simple biological neuron to the left. The neuron has dendrites that receive signals from other neurons. A cell body controls activation, and an axon carries an electrical impulse to the dendrites of other neurons. The artificial neuron to the right has a series of weighted inputs: a summing function that groups the inputs and a firing mechanism (F(Net)), which decides whether the inputs have reached a threshold, and, if so, the neuron will fire:

Neural networks are tolerant of noisy images and distortion, and so are useful when a black box classification method is needed for potentially degraded images. The next area to consider is the summation function for the neuron inputs. The following diagram shows the summation function called Net for neuron i. The connections between the neurons that have the weighting values, contain the stored knowledge of the network. Generally, a network will have an input layer, output layer, and a number...