Julia for Data Science [Video]

More Information
Learn
  • Get to grips with the basic data structures in Julia and learn about different development environments
  • Organize your code by writing Lisp-style macros and using modules
  • Manage, analyze, and work in depth with statistical data sets using the powerful DataFrames package
  • Perform statistical computations on data from different sources and visualize those using plotting packages
  • Apply different algorithms from decision trees and other packages to extract meaningful information from the iris dataset
  • Gain some valuable insights into interfacing Julia with an R application
About

Julia is an easy, fast, open source language that if written well performs nearly as well as low-level languages such as C and FORTRAN. Its design is a dance between specialization and abstraction, providing high machine performance without the sacrifice of human convenience. Julia is a fresh approach to technical computing, combining expertise from diverse fields of computational and computer science.

This video course walks you through all the steps involved in applying the Julia ecosystem to your own data science projects. We start with the basics and show you how to design and implement some of the general purpose features of Julia. Is fast development and fast execution possible at the same time? Julia provides the best of both worlds with its wide range of types, and our course covers this in depth. You will have organized and readable code by the end of the course by learning how to write Lisp style macros and modules.

The course demonstrates the power of the DataFrames package to manage, organize, and analyze data. It enables you to work with data from various sources, perform statistical calculations on them, and visualize their relationships in different kinds of plots through live demonstrations.

Julia for Data Science takes you from zero to hero, leaving you with the know-how required to apply

Style and Approach

This course provides in-depth content balanced with functional tutorials that put theory into practice. The focus of this course is to give you both a technical understanding and the practical experience that will allow you to use Julia for data science projects.

Features
  • Learn to use the machine learning algorithms in Julia to make better decisions and smarter actions in real time without human intervention
  • Get to grips with the specialized packages in Julia and leverage its performance capabilities to create efficient programs
  • Create your own modules and contribute to the Julia package system
Course Length 2 hours 41 minutes
ISBN 9781785882067
Date Of Publication 29 Mar 2016

Authors

Ivo Balbaert

Ivo Balbaert has been a lecturer in web programming and databases at CVO Antwerpen, a community college in Belgium. He received a Ph.D. in applied physics from the University of Antwerp in 1986. He worked for 20 years in the software industry as a developer and consultant in several companies, and for 10 years as project manager at the University Hospital of Antwerp. From 2000 onwards, he switched to partly teaching and partly developing software (at KHM Mechelen, CVO Antwerpen). He also wrote an introductory book in Dutch about developing in Ruby and Rails, Programmeren met Ruby en Rails, by Van Duuren Media. In 2012, he authored a book on the Go programming language, The Way To Go, by IUniverse. He wrote a number of introductory books for new programming languages, notably Dart, Julia, Rust, and Red, all published by Packt.