Not only, but also…
Julia was initially designed with scientific computing in mind and has made considerable strides in recent years in the fields of machine learning, optimization, solution of differential systems, and so on, all of which will be dealt with topics in the latter portion of this book.
However, Julia was originally seen as a vehicle for the emerging discipline of data science, possibly as an alternative or adjunct to more popular approaches, and it is worth remarking that practitioners in data science would be advised to see what Julia has to offer here as well.
Although the term data science was coined as early as the 1970s, it was only given prominence in 2001 by William S. Cleveland in his article, Data Science: An Action Plan for Expanding the Technical Areas of the Field of Statistics.
Almost in parallel with the development of Julia has been the growth in data science and the demand for data science practitioners.
What is data science?
People...
