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Apache Spark 2.x Machine Learning Cookbook

You're reading from  Apache Spark 2.x Machine Learning Cookbook

Product type Book
Published in Sep 2017
Publisher Packt
ISBN-13 9781783551606
Pages 666 pages
Edition 1st Edition
Languages
Concepts
Authors (5):
Mohammed Guller Mohammed Guller
Profile icon Mohammed Guller
LinkedIn
Author of Big Data Analytics with Spark - http://www.apress.com/9781484209653
See other products by Mohammed Guller
Siamak Amirghodsi Siamak Amirghodsi
Profile icon Siamak Amirghodsi
LinkedIn
Siamak Amirghodsi (Sammy) is interested in building advanced technical teams, executive management, Spark, Hadoop, big data analytics, AI, deep learning nets, TensorFlow, cognitive models, swarm algorithms, real-time streaming systems, quantum computing, financial risk management, trading signal discovery, econometrics, long-term financial cycles, IoT, blockchain, probabilistic graphical models, cryptography, and NLP.
See other products by Siamak Amirghodsi
Shuen Mei Shuen Mei
Profile icon Shuen Mei
LinkedIn
Shuen Mei is a big data analytic platforms expert with 15+ years of experience in designing, building, and executing large-scale, enterprise-distributed financial systems with mission-critical low-latency requirements. He is certified in the Apache Spark, Cloudera Big Data platform, including Developer, Admin, and HBase. He is also a certified AWS solutions architect with emphasis on peta-byte range real-time data platform systems.
See other products by Shuen Mei
Meenakshi Rajendran Meenakshi Rajendran
Profile icon Meenakshi Rajendran
LinkedIn
Meenakshi Rajendran is experienced in the end-to-end delivery of data analytics and data science products for leading financial institutions. Meenakshi holds a master's degree in business administration and is a certified PMP with over 13 years of experience in global software delivery environments. Her areas of research and interest are Apache Spark, cloud, regulatory data governance, machine learning, Cassandra, and managing global data teams at scale.
See other products by Meenakshi Rajendran
Broderick Hall Broderick Hall
Profile icon Broderick Hall
LinkedIn
Broderick Hall is a hands-on big data analytics expert and holds a masters degree in computer science with 20 years of experience in designing and developing complex enterprise-wide software applications with real-time and regulatory requirements at a global scale. He is a deep learning early adopter and is currently working on a large-scale cloud-based data platform with deep learning net augmentation.
See other products by Broderick Hall
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Table of Contents (20) Chapters

Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Practical Machine Learning with Spark Using Scala 2. Just Enough Linear Algebra for Machine Learning with Spark 3. Spark's Three Data Musketeers for Machine Learning - Perfect Together 4. Common Recipes for Implementing a Robust Machine Learning System 5. Practical Machine Learning with Regression and Classification in Spark 2.0 - Part I 6. Practical Machine Learning with Regression and Classification in Spark 2.0 - Part II 7. Recommendation Engine that Scales with Spark 8. Unsupervised Clustering with Apache Spark 2.0 9. Optimization - Going Down the Hill with Gradient Descent 10. Building Machine Learning Systems with Decision Tree and Ensemble Models 11. Curse of High-Dimensionality in Big Data 12. Implementing Text Analytics with Spark 2.0 ML Library 13. Spark Streaming and Machine Learning Library

About the Reviewer

Sumit Pal, who has authored SQL on Big Data - Technology, Architecture, and Innovations by Apress, has more than 22 years of experience in the software industry in various roles, spanning companies from startups to enterprises. 

Sumit is an independent consultant working with big data, data visualization, and data science, and he is a software architect building end-to-end data-driven analytic systems.

Sumit has worked for Microsoft (SQL server development team), Oracle (OLAP development team), and Verizon (big data analytics team) in a career spanning 22 years. Currently, he works for multiple clients advising them on their data architectures and big data solutions, and does hands-on coding with Spark, Scala, Java, and Python.

Sumit has spoken at the following Big Data Conferences:

  • Data Summit NY, May 2017
  • Big Data Symposium Boston, May 2017
  • Apache Linux Foundation, May 2016, Vancouver, Canada,
  • Data Center World, March 2016, Las Vegas
  • Chicago, Nov 2015
  • Big Data Conferences in Global Big Data Conference in Boston, Aug 2015

Sumit has also developed a Big Data Analyst Training course for Experfy, more details of which can be found at https://www.experfy.com/training/courses/big-data-analyst.

Sumit has an extensive experience in building scalable systems across the stack from middle tier and data tier to visualization for analytics applications, using big data and NoSQL DB. He has deep expertise in database internals, data warehouses, dimensional modeling, data science with Java and Python, and SQL. 

Sumit started his career as a part of the SQL Server Development Team at Microsoft in 1996-97 and then as a core server engineer for Oracle Corporation at their OLAP Development team in Burlington, MA.

Sumit has also worked at Verizon as an Associate Director for big data architecture, where he strategized, managed, architected, and developed platforms and solutions for analytics and machine learning applications. He has also served as a chief architect at ModelN/LeapfrogRX (2006-2013), where he architected the middle-tier core analytics platform with open source OLAP engine (Mondrian) on J2EE and solved some complex Dimensional ETL, Modeling, and performance optimization problems.

Sumit has MS and BS in computer science. He hiked to the Mt. Everest Base camp in Oct, 2016.

 

 

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Authors (5)

Left arrow icon
Profile icon Mohammed Guller
LinkedIn
Author of Big Data Analytics with Spark - http://www.apress.com/9781484209653
See other products by Mohammed Guller
Profile icon Siamak Amirghodsi
LinkedIn
Siamak Amirghodsi (Sammy) is interested in building advanced technical teams, executive management, Spark, Hadoop, big data analytics, AI, deep learning nets, TensorFlow, cognitive models, swarm algorithms, real-time streaming systems, quantum computing, financial risk management, trading signal discovery, econometrics, long-term financial cycles, IoT, blockchain, probabilistic graphical models, cryptography, and NLP.
See other products by Siamak Amirghodsi
Profile icon Shuen Mei
LinkedIn
Shuen Mei is a big data analytic platforms expert with 15+ years of experience in designing, building, and executing large-scale, enterprise-distributed financial systems with mission-critical low-latency requirements. He is certified in the Apache Spark, Cloudera Big Data platform, including Developer, Admin, and HBase. He is also a certified AWS solutions architect with emphasis on peta-byte range real-time data platform systems.
See other products by Shuen Mei
Profile icon Meenakshi Rajendran
LinkedIn
Meenakshi Rajendran is experienced in the end-to-end delivery of data analytics and data science products for leading financial institutions. Meenakshi holds a master's degree in business administration and is a certified PMP with over 13 years of experience in global software delivery environments. Her areas of research and interest are Apache Spark, cloud, regulatory data governance, machine learning, Cassandra, and managing global data teams at scale.
See other products by Meenakshi Rajendran
Profile icon Broderick Hall
LinkedIn
Broderick Hall is a hands-on big data analytics expert and holds a masters degree in computer science with 20 years of experience in designing and developing complex enterprise-wide software applications with real-time and regulatory requirements at a global scale. He is a deep learning early adopter and is currently working on a large-scale cloud-based data platform with deep learning net augmentation.
See other products by Broderick Hall
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