Apache Spark 2.x Machine Learning Cookbook

Simplify machine learning model implementations with Spark

• Solve the day-to-day problems of data science with Spark
• This unique cookbook consists of exciting and intuitive numerical recipes
• Optimize your work by acquiring, cleaning, analyzing, predicting, and visualizing your data

This book is for Scala developers with a fairly good exposure to and understanding of machine learning techniques, but lack practical implementations with Spark. A solid knowledge of machine learning algorithms is assumed, as well as hands-on experience of implementing ML algorithms with Scala. However, you do not need to be acquainted with the Spark ML libraries and ecosystem.

• Get to know how Scala and Spark go hand-in-hand for developers when developing ML systems with Spark
• Build a recommendation engine that scales with Spark
• Find out how to build unsupervised clustering systems to classify data in Spark
• Build machine learning systems with the Decision Tree and Ensemble models in Spark
• Deal with the curse of high-dimensionality in big data using Spark
• Implement Text analytics for Search Engines in Spark
• Streaming Machine Learning System implementation using Spark

Machine learning aims to extract knowledge from data, relying on fundamental concepts in computer science, statistics, probability, and optimization. Learning about algorithms enables a wide range of applications, from everyday tasks such as product recommendations and spam filtering to cutting edge applications such as self-driving