Use the advanced features of Julia to work with complex data
With the amount of data that is generated in the world these days, we are faced with the challenge of analyzing this data. Julia, which enjoys the benefits of a sophisticated compiler, parallel execution, and an all-encompassing mathematical function library, acts a a very good tool that helps us work with data more efficiently.
In this Learning Path, embark your journey, from the basics of Julia, right from installing it on your system and setting up the environment. You will then be introduced to the basic machine learning techniques, data science models, and concepts of parallel computing.
After completing this learning path, you will have acquired all the skills that will help you work with data effectively.
Prerequisites: The knowledge of the basic data science concepts is beneficial, although not necessary.
Resources: Code downloads and errata:
This path navigates across the following products (in sequential order):
Julia for Data Science (2h 41m)
Julia Solutions (2h 52m)