Siamak Amirghodsi - Apache Spark 2.x Machine Learning Cookbook

BIRMINGHAM - MUMBAI

Copyright 2017 Packt Publishing

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First published: September 2017

Production reference: 1200917

ISBN 978-1-78355-160-6

www.packtpub.com

Siamak Amirghodsi (Sammy) is a world-class senior technology executive leader with an entrepreneurial track record of overseeing big data strategies, cloud transformation, quantitative risk management, advanced analytics, large-scale regulatory data platforming, enterprise architecture, technology road mapping, multi-project execution, and organizational streamlining in Fortune 20 environments in a global setting.

Siamak is a hands-on big data, cloud, machine learning, and AI expert, and is currently overseeing the large-scale cloud data platforming and advanced risk analytics build out for a tier-1 financial institution in the United States. Siamak's interests include 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.

Siamak is fully certified on Cloudera's big data platform and follows Apache Spark, TensorFlow, Hadoop, Hive, Pig, Zookeeper, Amazon AWS, Cassandra, HBase, Neo4j, MongoDB, and GPU architecture, while being fully grounded in the traditional IBM/Oracle/Microsoft technology stack for business continuity and integration.

Siamak has a PMP designation. He holds an advanced degree in computer science and an MBA from the University of Chicago (ChicagoBooth), with emphasis on strategic management, quantitative finance, and econometrics.

Meenakshi Rajendran is a hands-on big data analytics and data governance manager with expertise in large-scale data platforming and machine learning program execution on a global scale. She 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. She not only understands the underpinnings of big data and data science technology but also has a solid understanding of the human side of the equation as well.

Meenakshis favorite languages are Python, R, Julia, and Scala. Her areas of research and interest are Apache Spark, cloud, regulatory data governance, machine learning, Cassandra, and managing global data teams at scale. In her free time, she dabbles in software engineering management literature, cognitive psychology, and chess for relaxation.

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 has an extensive experience in designing and building real-time financial applications for some of the largest financial institutions and exchanges in USA. He is a deep learning early adopter and is currently working on a large-scale cloud-based data platform with deep learning net augmentation.

Broderick has extensive experience working in healthcare, travel, real estate, and data center management. Broderick also enjoys his role as an adjunct professor, instructing courses in Java programming and object-oriented programming. He is currently focused on delivering real-time big data mission-critical analytics applications in the financial services industry.

Broderick has been actively involved with Hadoop, Spark, Cassandra, TensorFlow, and deep learning since the early days, while actively pursuing machine learning, cloud architecture, data platforms, data science, and practical applications in cognitive sciences. He enjoys programming in Scala, Python, R, Java, and Julia.

Shuen Mei is a big data analytic platforms expert with 15+ years of experience in the financial services industry. He is experienced 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.

Shuen is also a certified AWS solutions architect with emphasis on peta-byte range real-time data platform systems. Shuen is a skilled software engineer with extensive experience in delivering infrastructure, code, data architecture, and performance tuning solutions in trading and finance for Fortune 100 companies.

Shuen holds a master's degree in MIS from the University of Illinois. He actively follows Spark, TensorFlow, Hadoop, Spark, Cloud Architecture, Apache Flink, Hive, HBase, Cassandra, and related systems. He is passionate about Scala, Python, Java, Julia, cloud computing, machine learning algorithms, and deep learning at scale.

Sumit Pal, who has authored SQL on Big Data - Technology, Architecture, and Innovations