Apache Spark Machine Learning Blueprints
Alex Liu
Verkauft von THE SAINT BOOKSTORE, Southport, Vereinigtes Königreich
AbeBooks-Verkäufer seit 14. Juni 2006
Neu - Softcover
Zustand: Neu
Anzahl: Mehr als 20 verfügbar
In den Warenkorb legenVerkauft von THE SAINT BOOKSTORE, Southport, Vereinigtes Königreich
AbeBooks-Verkäufer seit 14. Juni 2006
Zustand: Neu
Anzahl: Mehr als 20 verfügbar
In den Warenkorb legenThis item is printed on demand. New copy - Usually dispatched within 5-9 working days 526.
Bestandsnummer des Verkäufers C9781785880391
There's a reason why Apache Spark has become one of the most popular tools in Machine Learning – its ability to handle huge datasets at an impressive speed means you can be much more responsive to the data at your disposal. This book shows you Spark at its very best, demonstrating how to connect it with R and unlock maximum value not only from the tool but also from your data.
Packed with a range of project "blueprints" that demonstrate some of the most interesting challenges that Spark can help you tackle, you'll find out how to use Spark notebooks and access, clean, and join different datasets before putting your knowledge into practice with some real-world projects, in which you will see how Spark Machine Learning can help you with everything from fraud detection to analyzing customer attrition. You'll also find out how to build a recommendation engine using Spark's parallel computing powers.
Alex Liu is an expert in research methods and data science. He is currently one of IBM's leading experts in Big Data analytics and also a lead data scientist, where he serves big corporations, develops Big Data analytics IPs, and speaks at industrial conferences such as STRATA, Insights, SMAC, and BigDataCamp. In the past, Alex served as chief or lead data scientist for a few companies, including Yapstone, RS, and TRG. Before this, he was a lead consultant and director at RMA, where he provided data analytics consultation and training to many well-known organizations, including the United Nations, Indymac, AOL, Ingram Micro, GEM, Farmers Insurance, Scripps Networks, Sears, and USAID. At the same time, he taught advanced research methods to PhD candidates at University of Southern California and University of California at Irvine. Before this, he worked as a managing director for CATE/GEC and as a research fellow for the Asia/Pacific Research Center at Stanford University. Alex has a Ph.D. in quantitative sociology and a master's degree of science in statistical computing from Stanford University.
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