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

The game plan

We're onto the last stage of our project—the web UI. Let's start by discussing the spec; we need to lay out the blueprint before we can proceed with the implementation.

The player will start on the landing page. This will display the rules and will provide options for launching a new game, allowing the user to choose a difficulty level. Following this starting point, the player will be redirected to the new game page. Here, taking into account the selected difficulty level, we'll bootstrap a new game session by fetching the articles with the algorithm we wrote in the previous chapter. Once we pick the articles that represent the Six Degrees of Wikipedia, we will display a heading with the game's objective—the titles of the start and end articles. We'll also display the content of the first article, thus kickstarting the game. When the player clicks on a link in this article, we have to respond accordingly by checking if the player has found the end article and won the game....