Apache Spark Machine Learning Cookbook by Siamak Amirghodsi

By Siamak Amirghodsi

Over eighty recipes to simplify computer studying version implementations with Spark

About This Book

  • Solve the daily difficulties of knowledge technology with Spark
  • This special cookbook involves intriguing and intuitive numerical recipes
  • Optimize your paintings by means of buying, cleansing, examining, predicting, and visualizing your data

Who This booklet Is For

This ebook is for Scala builders with a reasonably reliable publicity to and figuring out of laptop studying suggestions, yet lack useful implementations with Spark. a fantastic wisdom of desktop studying algorithms is believed, in addition to hands-on event of enforcing ML algorithms with Scala. notwithstanding, you don't need to be conversant in the Spark ML libraries and ecosystem.

What you are going to Learn

  • Get to understand how Scala and Spark move hand-in-hand for builders whilst constructing ML platforms with Spark
  • Build a advice engine that scales with Spark
  • Find out the best way to construct unsupervised clustering platforms to categorise information in Spark
  • Build computing device studying structures with the choice Tree and Ensemble types in Spark
  • Deal with the curse of high-dimensionality in large info utilizing Spark
  • Implement textual content analytics for se's in Spark
  • Streaming desktop studying process implementation utilizing Spark

In Detail

Machine studying goals to extract wisdom from info, counting on basic techniques in laptop technology, information, likelihood, and optimization. studying approximately algorithms allows quite a lot of functions, from daily projects similar to product thoughts and unsolicited mail filtering to bleeding part purposes corresponding to self-driving automobiles and customized medication. you are going to achieve hands-on event of making use of those rules utilizing Apache Spark, a cluster computing process compatible for large-scale computer studying tasks.

This e-book starts with a brief evaluate of developing the mandatory IDEs to facilitate the execution of code examples that might be coated. It additionally highlights a few key matters builders face whereas considering Scala for computer studying and through the swap over to Spark. We growth through uncovering many of the Spark APIs and the implementation of ML algorithms with constructing class platforms, suggestion engines, clustering and studying structures. in the direction of the ultimate chapters, we’ll specialize in development high-end purposes and clarify numerous unsupervised methodologies and demanding situations to take on whilst enforcing with monstrous information ML systems.

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