By Jayani Withanawasam
About This Book
- Apply computer studying algorithms successfully in creation environments with Apache Mahout
- Gain greater insights into huge, advanced, and scalable datasets
- Fast-paced instructional, masking the middle techniques of Apache Mahout to enforce laptop studying on great Data
Who This publication Is For
If you're a Java developer or facts scientist, have not labored with Apache Mahout sooner than, and wish to wake up to hurry on enforcing computer studying on titanic facts, then this is often the fitting advisor for you.
What you'll Learn
- Get all started with the basics of massive information, batch, and real-time information processing with an advent to Mahout and its applications
- Understand the most important computer studying recommendations at the back of algorithms in Apache Mahout
- Apply laptop studying algorithms supplied via Apache Mahout in real-world sensible scenarios
- Implement and review widely-used clustering, type, and suggestion algorithms utilizing Apache Mahout
- Discover information and tips to enhance the accuracy and function of your results
- Set up Apache Mahout in a construction atmosphere with Apache Hadoop
- Glance on the Spark DSL developments in Apache Mahout 1.0
- Provide dynamic and interactive info visualizations for Apache Mahout
- Build a suggestion engine for real-time use instances and use user-based and item-based advice algorithms
Apache Mahout is a scalable computer studying library with algorithms for clustering, type, and suggestions. It empowers clients to research styles in huge, diversified, and complicated datasets speedier and extra scalably.
This ebook is an all-inclusive advisor to reading huge and complicated datasets utilizing Apache Mahout. It explains complex yet very potent computer studying algorithms easily, relating to real-world sensible examples.
Starting from the elemental thoughts of computing device studying and Apache Mahout, this ebook publications you thru Apache Mahout's implementations of laptop studying strategies together with category, clustering, and proposals. in this interesting walkthrough, real-world purposes, a various variety of well known algorithms and their implementations, code examples, review ideas, and top practices are given for every approach. ultimately, you'll examine vdata visualization innovations for Apache Mahout to convey your facts to life.
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Additional resources for Apache Mahout Essentials
Apache Mahout Essentials by Jayani Withanawasam