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Scala for Machine Learning

You're reading from   Scala for Machine Learning Leverage Scala and Machine Learning to construct and study systems that can learn from data

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Product type Paperback
Published in Dec 2014
Publisher
ISBN-13 9781783558742
Length 624 pages
Edition 1st Edition
Languages
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Author (1):
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Patrick R. Nicolas Patrick R. Nicolas
Author Profile Icon Patrick R. Nicolas
Patrick R. Nicolas
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Table of Contents (15) Chapters Close

Preface 1. Getting Started 2. Hello World! FREE CHAPTER 3. Data Preprocessing 4. Unsupervised Learning 5. Naïve Bayes Classifiers 6. Regression and Regularization 7. Sequential Data Models 8. Kernel Models and Support Vector Machines 9. Artificial Neural Networks 10. Genetic Algorithms 11. Reinforcement Learning 12. Scalable Frameworks A. Basic Concepts Index

Akka


The Akka framework extends the original Actor model in Scala by adding extraction capabilities such as support for typed Actor, message dispatching, routing, load balancing, and partitioning, as well as supervision and configurability [12:7].

The Akka framework can be downloaded from the http://akka.io/ website or through the Typesafe Activator at http://www.typesafe.com/platform.

Akka simplifies the implementation of the Actor model by encapsulating some of the details of Scala Actor in the akka.actor.Actor and akka.actor.ActorSystem classes.

The three methods you want to override are as follows:

  • prestart: This is an optional method that is invoked to initialize all the necessary resources such as file or database connection before the Actor is executed

  • receive: This method defines the Actor's behavior and returns a partial function of the PartialFunction[Any, Unit] type

  • postStop: This is an optional method to clean up resources such as releasing memory, closing database connections,...

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