Scala: Applied Machine Learning

Leverage the power of Scala and master the art of building, improving, and validating scalable machine learning and AI applications using Scala's most advanced and finest features.
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Scala: Applied Machine Learning

Pascal Bugnion, Patrick R. Nicolas, Alex Kozlov

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Leverage the power of Scala and master the art of building, improving, and validating scalable machine learning and AI applications using Scala's most advanced and finest features.
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Book Details

ISBN 139781787126640
Paperback1265 pages

Book Description

This Learning Path aims to put the entire world of machine learning with Scala in front of you.

Scala for Data Science, the first module in this course, is a tutorial guide that provides tutorials on some of the most common Scala libraries for data science, allowing you to quickly get up to speed building data science and data engineering solutions.

The second course, Scala for Machine Learning guides you through the process of building AI applications with diagrams, formal mathematical notation, source code snippets, and useful tips. A review of the Akka framework and Apache Spark clusters concludes the tutorial.

The next module, Mastering Scala Machine Learning, is the final step in this course. It will take your knowledge to next level and help you use the knowledge to build advanced applications such as social media mining, intelligent news portals, and more. After a quick refresher on functional programming concepts using REPL, you will see some practical examples of setting up the development environment and tinkering with data. We will then explore working with Spark and MLlib using k-means and decision trees.

By the end of this course, you will be a master at Scala machine learning and have enough expertise to be able to build complex machine learning projects using Scala.

This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:

  • Scala for Data Science, Pascal Bugnion
  • Scala for Machine Learning, Patrick Nicolas
  • Mastering Scala Machine Learning, Alex Kozlov

Table of Contents

Chapter 4: Parallel Collections and Futures
Chapter 34: Integrating Scala with R and Python

What You Will Learn

  • Create Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizations
  • Deploy scalable parallel applications using Apache Spark, loading data from HDFS or Hive
  • Solve big data problems with Scala parallel collections, Akka actors, and Apache Spark clusters
  • Apply key learning strategies to perform technical analysis of financial markets
  • Understand the principles of supervised and unsupervised learning in machine learning
  • Work with unstructured data and serialize it using Kryo, Protobuf, Avro, and AvroParquet
  • Construct reliable and robust data pipelines and manage data in a data-driven enterprise
  • Implement scalable model monitoring and alerts with Scala

Authors

Table of Contents

Chapter 4: Parallel Collections and Futures
Chapter 34: Integrating Scala with R and Python

Book Details

ISBN 139781787126640
Paperback1265 pages
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