Scala Machine Learning Projects

More Information
Learn
  • Apply advanced regression techniques to boost the performance of predictive models
  • Use different classification algorithms for business analytics
  • Generate trading strategies for Bitcoin and stock trading using ensemble techniques
  • Train Deep Neural Networks (DNN) using H2O and Spark ML
  • Utilize NLP to build scalable machine learning models
  • Learn how to apply reinforcement learning algorithms such as Q-learning for developing ML application
  • Learn how to use autoencoders to develop a fraud detection application
  • Implement LSTM and CNN models using DeepLearning4j and MXNet
About

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.

Features
  • Explore machine learning techniques with prominent open source Scala libraries such as Spark ML, H2O, MXNet, Zeppelin, and DeepLearning4j
  • Solve real-world machine learning problems by delving complex numerical computing with Scala functional programming in a scalable and faster way
  • Cover all key aspects such as collection, storing, processing, analyzing, and evaluation required to build and deploy machine models on computing clusters using Scala Play framework.
Page Count 470
Course Length 14 hours 6 minutes
ISBN 9781788479042
Date Of Publication 31 Jan 2018

Authors

Md. Rezaul Karim

Md. Rezaul Karim is a researcher, author, and data science enthusiast with a strong computer science background, coupled with 10 years of research and development experience in machine learning, deep learning, and data mining algorithms to solve emerging bioinformatics research problems by making them explainable. He is passionate about applied machine learning, knowledge graphs, and explainable artificial intelligence (XAI). Currently, he is working as 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. Previously, he worked as a lead software engineer at Samsung Electronics, Korea.