By Siamak Amirghodsi
Over eighty recipes to simplify computer studying version implementations with Spark
About This Book
- Solve the daily difficulties of knowledge technological know-how with Spark
- This detailed cookbook involves fascinating and intuitive numerical recipes
- Optimize your paintings by means of buying, cleansing, interpreting, predicting, and visualizing your data
Who This ebook Is For
This e-book is for Scala builders with a reasonably strong publicity to and knowing of desktop studying suggestions, yet lack functional implementations with Spark. an excellent wisdom of computing device studying algorithms is believed, in addition to hands-on event of enforcing 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 understand how Scala and Spark move hand-in-hand for builders whilst constructing ML structures with Spark
- Build a suggestion engine that scales with Spark
- Find out the right way to construct unsupervised clustering structures to categorise info in Spark
- Build desktop studying structures with the choice Tree and Ensemble types in Spark
- Deal with the curse of high-dimensionality in gigantic facts 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 info, hoping on primary recommendations in machine technology, records, likelihood, and optimization. studying approximately algorithms permits quite a lot of purposes, from daily projects akin to product thoughts and junk mail filtering to bleeding aspect purposes comparable to self-driving automobiles and custom-made drugs. you'll achieve hands-on adventure of employing those rules utilizing Apache Spark, a cluster computing method compatible for large-scale desktop studying tasks.
This publication starts off with a short evaluation of establishing the mandatory IDEs to facilitate the execution of code examples that would be coated. It additionally highlights a few key concerns builders face whereas puzzling over Scala for computer 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 category platforms, advice engines, clustering and studying platforms. in the direction of the ultimate chapters, we’ll concentrate on development high-end functions and clarify a variety of unsupervised methodologies and demanding situations to take on while imposing with significant information ML systems.
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Apache Spark Machine Learning Cookbook by Siamak Amirghodsi