Book Image

Scala Machine Learning Projects

Book Image

Scala Machine Learning Projects

Overview of this book

Machine learning has had a huge impact on academia and industry by turning data into actionable information. Scala has seen a steady rise in adoption over the past few years, especially in the fields of data science and analytics. This book is for data scientists, data engineers, and deep learning enthusiasts who have a background in complex numerical computing and want to know more hands-on machine learning application development. If you're well versed in machine learning concepts and want to expand your knowledge by delving into the practical implementation of these concepts using the power of Scala, then this book is what you need! Through 11 end-to-end projects, you will be acquainted with popular machine learning libraries such as Spark ML, H2O, DeepLearning4j, and MXNet. At the end, you will be able to use numerical computing and functional programming to carry out complex numerical tasks to develop, build, and deploy research or commercial projects in a production-ready environment.
Table of Contents (17 chapters)
Title Page
Packt Upsell


About the author

Md. Rezaul Karim is a Research Scientist at Fraunhofer FIT, Germany. He is also a PhD candidate at RWTH Aachen University, Germany. Before joining FIT, he worked as a Researcher at the Insight Centre for Data Analytics, Ireland. Before that, he worked as a Lead Engineer at Samsung Electronics, Korea.

He has 9 years of R&D experience with C++, Java, R, Scala, and Python. He has published several research papers concerning bioinformatics, big data, and deep learning. He has practical working experience with Spark, Zeppelin, Hadoop, Keras, Scikit-Learn, TensorFlow, DeepLearning4j, MXNet, and H2O.


About the reviewer

Dave Wentzel is the chief technology officer of Capax Global, a premier Microsoft consulting partner. Dave is responsible for setting the strategy and defining service offerings and capabilities for the data platform and Azure practice at Capax. He also works directly with clients to help them with their big data journeys. He is a frequent blogger and speaker on big data and data science topics.


Sumit Pal is a published author with Apress. He has more than 22 years of experience in software from startups to enterprises and is an independent consultant working with big data, data visualization, and data science. He builds end-to-end data-driven analytic systems.

Sumit has worked for Microsoft (SQLServer), Oracle (OLAP Kernel), and Verizon. He advises clients on their data architectures and build solutions in Spark and Scala. He has spoken at multiple conferences in North America and Europe and has developed a big data analyst training for Experfy. He has MS and BS in computer science.





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