Julia for High-Performance Data Analytics
Julia has a rich ecosystem of libraries aimed towards scientific computing and a powerful builtin package manager to install and manage their dependencies. Thanks to a rapidly growing ecosystem of packages for data science and machine learning, Julia is quickly gaining ground in both academic and industrial domains which deal with large datasets.
Overview
This lesson starts with a discussion of working with data in Julia, how to use the DataFrames.jl package and how to visualise data. It then moves on to linear algebra approaches, followed by classical machine learning approaches as well as deep learning methods with an example of scientific ML. Finally, key aspects of regression, time series prediction and analysis is covered.
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