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Scala Machine Learning Projects

You're reading from Scala Machine Learning Projects Build real-world machine learning and deep learning projects with Scala

Product type Paperback

Published in Jan 2018

Publisher Packt

ISBN-13 9781788479042

Length 470 pages

Edition 1st Edition

Languages

Scala

Tools

Apache Spark

Concepts

Deep Learning

Author (1):

Md. Rezaul Karim

View More author details

Table of Contents (13) Chapters

Preface

1. Analyzing Insurance Severity Claims

2. Analyzing and Predicting Telecommunication Churn FREE CHAPTER

3. High Frequency Bitcoin Price Prediction from Historical and Live Data

4. Population-Scale Clustering and Ethnicity Prediction

5. Topic Modeling - A Better Insight into Large-Scale Texts

6. Developing Model-based Movie Recommendation Engines

7. Options Trading Using Q-learning and Scala Play Framework

8. Clients Subscription Assessment for Bank Telemarketing using Deep Neural Networks

9. Fraud Analytics Using Autoencoders and Anomaly Detection

10. Human Activity Recognition using Recurrent Neural Networks

11. Image Classification using Convolutional Neural Networks

12. Other Books You May Enjoy

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Who this book is for

If you want to leverage the power of both Scala and open source libraries such as Spark ML, Deeplearning4j, H2O, MXNet, and Zeppelin to make sense of Big Data, then this book is for you. A strong understanding of Scala and the Scala Play Framework is recommended. Basic familiarity with ML techniques will be an added advantage.

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Authors (1)

Karim

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.

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