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Julia Programming Projects

You're reading from   Julia Programming Projects Learn Julia 1.x by building apps for data analysis, visualization, machine learning, and the web

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781788292740
Length 500 pages
Edition 1st Edition
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Author (1):
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Adrian Salceanu Adrian Salceanu
Author Profile Icon Adrian Salceanu
Adrian Salceanu
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Julia Programming FREE CHAPTER 2. Creating Our First Julia App 3. Setting Up the Wiki Game 4. Building the Wiki Game Web Crawler 5. Adding a Web UI for the Wiki Game 6. Implementing Recommender Systems with Julia 7. Machine Learning for Recommender Systems 8. Leveraging Unsupervised Learning Techniques 9. Working with Dates, Times, and Time Series 10. Time Series Forecasting 11. Creating Julia Packages 12. Other Books You May Enjoy

Classifying recommender systems

Different business needs—from suggesting related products after buying your new laptop, to compiling the perfect driving playlist, to helping you reconnect with long lost schoolmates—led to the development of different recommendation algorithms. A key part of rolling out a recommender system is picking the right approach for the problem at hand to fully take advantage of the data available. We'll take a look at the most common and most successful algorithms.

Learning about non-personalized, stereotyped, and personalized recommendations

The simplest types of recommendations, from a technical and algorithmic perspective, are the non-personalized ones. That is, they are not customized...

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