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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

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781788479042
Length 470 pages
Edition 1st Edition
Languages
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Author (1):
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Md. Rezaul Karim Md. Rezaul Karim
Author Profile Icon Md. Rezaul Karim
Md. Rezaul Karim
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Table of Contents (13) Chapters Close

Preface 1. Analyzing Insurance Severity Claims FREE CHAPTER 2. Analyzing and Predicting Telecommunication Churn 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

Developing Model-based Movie Recommendation Engines

Netflix is an American entertainment company founded by Reed Hastings and Marc Randolph on August 29, 1997, in Scotts Valley, California. It specializes in and provides streaming media, video-on-demand online, and DVD by mail. In 2013, Netflix expanded into film and television production, as well as online distribution. Netflix uses a model-based collaborative filtering approach for real-time movie recommendation for its subscribers.

In this chapter, we will see two end-to-end projects and develop a model for item-based collaborative filtering for movie similarity measurement and a model-based movie recommendation engine with Spark that recommends movies for new users. We will see how to interoperate between ALS and matrix factorization (MF) for these two scalable movie recommendation engines. We will use the movie lens dataset...

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