Summary

This chapter covered a diverse range of topics arising from the discipline of scientific computing, with a certain amount of cherry-picking on my part. Julia is now especially blessed with several packages that can be applied to scientific problems, so the reader is encouraged to look at the various community groups for additional information. We began by looking at classical linear algebra problems, the solutions of which are provided by routines from within the Julia BASE and STDLIB systems.

For the remaining sections, we turned to a variety of packages and applied them to examples from signal processing, optimization, and the solution of ordinary and stochastic DEs and touched upon the support Julia provides for the differentiation and integration of functions.

Finally, we looked at the solution of problems such as those that have a random (stochastic) component and saw how this can be simulated by various packages within Julia.

In the next chapter, we will have...