In this chapter, we saw how Julia proves its mettle in the field of numerical and statistical computations. We saw how data from various sources can be read and written using Julia's built-in features as well as how to use DataFrames for our own advantage. Next, we saw how linear algebra and differential equations can be solved using some of the most advanced mathematical packages. Later on, Statistics proved to be an area of deep interest for Julia developers, as we saw how easy it is for someone coming from a traditional language background to easily pick up stats in Julia. Lastly, we talked about some optimization problems and how they can be solved in Julia.
Coming up, in the next chapter, we will see how to make more sense out of data using graphs and what packages in Julia can be used to complete the job.
