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


Web scraping is a key component of data mining and Julia provides a powerful toolbox for handling these tasks. In this chapter, we addressed the fundamentals of building a web crawler. We learned how to request web pages with a Julia web client and how to read the responses, how to work with Julia's powerful Dict data structure to read HTTP information, how to make our software more resilient by handling errors, how to better organize our code by writing functions and documenting them, and how to use conditional logic to make decisions.

Armed with this knowledge, we built the first version of our web crawler. In the next chapter, we will improve it and will use it to extract the data for our upcoming Wiki game. In the process, we'll dive deeper into the language, learning about types, methods and modules, and how to interact with relational databases.