By Siamak Amirghodsi
Over eighty recipes to simplify desktop studying version implementations with Spark
About This Book
- Solve the daily difficulties of information technology with Spark
- This special cookbook comprises fascinating and intuitive numerical recipes
- Optimize your paintings through buying, cleansing, examining, predicting, and visualizing your data
Who This e-book Is For
This e-book is for Scala builders with a reasonably strong publicity to and figuring out of computing device studying suggestions, yet lack functional implementations with Spark. a pretty good wisdom of laptop studying algorithms is thought, in addition to hands-on adventure of enforcing ML algorithms with Scala. notwithstanding, you don't want to be conversant in 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 platforms with Spark
- Build a suggestion engine that scales with Spark
- Find out the best way to construct unsupervised clustering structures to categorise facts in Spark
- Build desktop studying structures with the choice Tree and Ensemble versions in Spark
- Deal with the curse of high-dimensionality in substantial facts utilizing Spark
- Implement textual content analytics for se's in Spark
- Streaming desktop studying process implementation utilizing Spark
Machine studying goals to extract wisdom from facts, counting on basic strategies in desktop technological know-how, information, chance, and optimization. studying approximately algorithms allows quite a lot of functions, from daily projects corresponding to product innovations and junk mail filtering to bleeding area purposes comparable to self-driving vehicles and customized medication. you are going to achieve hands-on adventure of utilizing those rules utilizing Apache Spark, a cluster computing approach like minded for large-scale computer studying tasks.
This ebook starts off with a short review of establishing the mandatory IDEs to facilitate the execution of code examples that may be coated. It additionally highlights a few key concerns builders face whereas considering Scala for desktop studying and through the change over to Spark. We development through uncovering some of the Spark APIs and the implementation of ML algorithms with constructing type platforms, suggestion engines, clustering and studying platforms. in the direction of the ultimate chapters, we’ll concentrate on construction high-end purposes and clarify quite a few unsupervised methodologies and demanding situations to take on whilst imposing with great information ML systems.
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Additional info for Apache Spark Machine Learning Cookbook
Apache Spark Machine Learning Cookbook by Siamak Amirghodsi