By Siamak Amirghodsi
Over eighty recipes to simplify computing device studying version implementations with Spark
About This Book
- Solve the daily difficulties of information technology with Spark
- This distinct cookbook includes intriguing and intuitive numerical recipes
- Optimize your paintings via buying, cleansing, reading, predicting, and visualizing your data
Who This e-book Is For
This publication is for Scala builders with a pretty reliable publicity to and knowing of computer studying innovations, yet lack functional implementations with Spark. an exceptional wisdom of computer studying algorithms is believed, in addition to hands-on event of imposing ML algorithms with Scala. even though, you don't want to be conversant in the Spark ML libraries and ecosystem.
What you'll Learn
- Get to understand how Scala and Spark pass hand-in-hand for builders while constructing ML structures with Spark
- Build a advice engine that scales with Spark
- Find out how one can construct unsupervised clustering structures to categorise facts in Spark
- Build computing device studying platforms with the choice Tree and Ensemble versions in Spark
- Deal with the curse of high-dimensionality in great info utilizing Spark
- Implement textual content analytics for se's in Spark
- Streaming desktop studying approach implementation utilizing Spark
Machine studying goals to extract wisdom from facts, hoping on primary options in desktop technology, records, likelihood, and optimization. studying approximately algorithms permits quite a lot of purposes, from daily initiatives resembling product concepts and unsolicited mail filtering to bleeding part purposes comparable to self-driving vehicles and custom-made drugs. you'll achieve hands-on event of utilizing those rules utilizing Apache Spark, a cluster computing approach well matched for large-scale computer studying tasks.
This publication starts off with a short review of constructing the mandatory IDEs to facilitate the execution of code examples that might be lined. It additionally highlights a few key concerns builders face whereas puzzling over Scala for desktop studying and through the change over to Spark. We growth by way of uncovering some of the Spark APIs and the implementation of ML algorithms with constructing category platforms, suggestion engines, clustering and studying structures. in the direction of the ultimate chapters, we’ll specialize in construction high-end purposes and clarify quite a few unsupervised methodologies and demanding situations to take on while enforcing with substantial info ML systems.
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Additional info for Apache Spark Machine Learning Cookbook
Apache Spark Machine Learning Cookbook by Siamak Amirghodsi