By Siamak Amirghodsi
Over eighty recipes to simplify desktop studying version implementations with Spark
About This Book
- Solve the day by day difficulties of knowledge technology with Spark
- This certain cookbook involves intriguing and intuitive numerical recipes
- Optimize your paintings through buying, cleansing, examining, predicting, and visualizing your data
Who This e-book Is For
This publication is for Scala builders with a pretty reliable publicity to and figuring out of computer studying strategies, yet lack functional implementations with Spark. an outstanding wisdom of computer studying algorithms is believed, in addition to hands-on adventure of imposing ML algorithms with Scala. despite the fact that, you don't need to be accustomed to the Spark ML libraries and ecosystem.
What you are going to Learn
- Get to grasp how Scala and Spark cross hand-in-hand for builders while constructing ML structures with Spark
- Build a suggestion engine that scales with Spark
- Find out tips on how to construct unsupervised clustering structures to categorise facts in Spark
- Build desktop studying platforms with the choice Tree and Ensemble types in Spark
- Deal with the curse of high-dimensionality in enormous info utilizing Spark
- Implement textual content analytics for se's in Spark
- Streaming laptop studying approach implementation utilizing Spark
Machine studying goals to extract wisdom from information, hoping on primary recommendations in laptop technology, statistics, chance, and optimization. studying approximately algorithms allows a variety of purposes, from daily initiatives equivalent to product techniques and junk mail filtering to bleeding area purposes akin to self-driving autos and custom-made medication. you'll achieve hands-on adventure of utilizing those rules utilizing Apache Spark, a cluster computing approach well matched for large-scale desktop studying tasks.
This ebook starts with a brief evaluation of developing the required IDEs to facilitate the execution of code examples that may be lined. It additionally highlights a few key matters builders face whereas considering Scala for desktop studying and through the change over to Spark. We growth through uncovering a number of the Spark APIs and the implementation of ML algorithms with constructing type platforms, advice engines, clustering and studying structures. in the direction of the ultimate chapters, we’ll specialise in construction high-end purposes and clarify a variety of unsupervised methodologies and demanding situations to take on whilst imposing with huge info ML systems.
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Extra resources for Apache Spark Machine Learning Cookbook
Apache Spark Machine Learning Cookbook by Siamak Amirghodsi