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Book Overview & Buying
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Table Of Contents
Scala Machine Learning Projects
By :
Scala Machine Learning Projects
By:
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 (13 chapters)
Preface
Free Chapter
Analyzing Insurance Severity Claims
Analyzing and Predicting Telecommunication Churn
High Frequency Bitcoin Price Prediction from Historical and Live Data
Population-Scale Clustering and Ethnicity Prediction
Topic Modeling - A Better Insight into Large-Scale Texts
Developing Model-based Movie Recommendation Engines
Options Trading Using Q-learning and Scala Play Framework
Clients Subscription Assessment for Bank Telemarketing using Deep Neural Networks
Fraud Analytics Using Autoencoders and Anomaly Detection
Human Activity Recognition using Recurrent Neural Networks
Image Classification using Convolutional Neural Networks
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