By Alex Liu
- Customize Apache Spark and R to suit your analytical wishes in purchaser learn, fraud detection, chance analytics, and advice engine development
- Develop a suite of sensible desktop studying functions that may be applied in real-life projects
- A entire, project-based advisor to enhance and refine your predictive types for functional implementation
There's a the reason is, Apache Spark has develop into some of the most renowned instruments in computer studying – its skill to address large datasets at a powerful velocity potential you'll be even more conscious of the information at your disposal. This publication indicates you Spark at its absolute best, demonstrating tips to attach it with R and free up greatest price not just from the software but additionally out of your data.
Packed with a number of venture "blueprints" that reveal essentially the most fascinating demanding situations that Spark might be useful take on, you can find out tips on how to use Spark notebooks and entry, fresh, and sign up for varied datasets sooner than placing your wisdom into perform with a few real-world tasks, within which one can find how Spark computer studying can help with every little thing from fraud detection to studying purchaser attrition. you are going to additionally tips to construct a suggestion engine utilizing Spark's parallel computing powers.
What you are going to learn
- Set up Apache Spark for desktop studying and detect its awesome processing power
- Combine Spark and R to release certain company insights crucial for selection making
- Build laptop studying platforms with Spark that could become aware of fraud and examine monetary risks
- Build predictive types targeting shopper scoring and repair ranking
- Build a suggestion platforms utilizing SPSS on Apache Spark
- Tackle parallel computing and learn the way it may help your desktop studying projects
- Turn open info and conversation info into actionable insights via using quite a few types of computer learning
About the Author
Alex Liu is knowledgeable in examine equipment and information technology. he's at present one in all IBM's best specialists in huge facts analytics and likewise a lead information scientist, the place he serves gigantic agencies, develops massive information analytics IPs, and speaks at commercial meetings comparable to STRATA, Insights, SMAC, and BigDataCamp. long ago, Alex served as leader or lead info scientist for a couple of businesses, together with Yapstone, RS, and TRG. sooner than this, he was once a lead advisor and director at RMA, the place he supplied facts analytics session and coaching to many recognized businesses, together with the United countries, Indymac, AOL, Ingram Micro, GEM, Farmers assurance, Scripps Networks, Sears, and USAID. even as, he taught complex examine easy methods to PhD applicants at collage of Southern California and collage of California at Irvine. earlier than this, he labored as a dealing with director for CATE/GEC and as a learn fellow for the Asia/Pacific examine middle at Stanford college. Alex has a Ph.D. in quantitative sociology and a master's measure of technological know-how in statistical computing from Stanford University.
Table of Contents
- Spark for computing device Learning
- Data instruction for Spark ML
- A Holistic View on Spark
- Fraud Detection on Spark
- Risk Scoring on Spark
- Churn Prediction on Spark
- Recommendations on Spark
- Learning Analytics on Spark
- City Analytics on Spark
- Learning Telco info on Spark
- Modeling Open facts on Spark
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Extra resources for Apache Spark Machine Learning Blueprints
Apache Spark Machine Learning Blueprints by Alex Liu