Book Image

Julia Programming Projects

By : Adrian Salceanu
Book Image

Julia Programming Projects

By: Adrian Salceanu

Overview of this book

Julia is a new programming language that offers a unique combination of performance and productivity. Its powerful features, friendly syntax, and speed are attracting a growing number of adopters from Python, R, and Matlab, effectively raising the bar for modern general and scientific computing. After six years in the making, Julia has reached version 1.0. Now is the perfect time to learn it, due to its large-scale adoption across a wide range of domains, including fintech, biotech, education, and AI. Beginning with an introduction to the language, Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames. You will explore functions and the type system, methods, and multiple dispatch while building a web scraper and a web app. Next, you'll delve into machine learning, where you'll build a books recommender system. You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database. After metaprogramming, the final chapters will discuss dates and time, time series analysis, visualization, and forecasting. We'll close with package development, documenting, testing and benchmarking. By the end of the book, you will have gained the practical knowledge to build real-world applications in Julia.
Table of Contents (19 chapters)
Title Page
Copyright and Credits
About Packt

Chapter 6. Implementing Recommender Systems with Julia

In the previous chapters, we took a deep dive into data mining and web development with Julia. I hope you enjoyed a few relaxing rounds of Six Degrees of Wikipedia while discovering some interesting articles. Randomly poking through the millions of Wikipedia articles as part of a game is a really fun way to stumble upon interesting new content. Although I'm sure that, at times, you've noticed that not all the articles are equally good—maybe they're stubs, or subjective, or not so well written, or simply irrelevant to you. If we were able to learn about each player's individual interests, we could filter out certain Wikipedia articles, which would turn each game session into a wonderful journey of discovery.

It turns out that we're not the only ones struggling with this—information discovery is a multibillion-dollar problem, regardless of whether it's articles, news, books, music, movies, hotels, or really any kind of product or service...