Mastering Julia

Summary

This chapter has covered a diverse range of topics arising from the discipline of scientific computing.

We began by looking at classical linear algebra problems, the solutions of which are provided by routines from within the Julia base system. 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 partial differential equations.

Finally, we turned to an area in which the use of Julia is particularly well suited, the solution of non-vectorized problems such as those arising from stochastic processes modeled by Monte Carlo methods.

In the next chapter, we will look in greater detail at the question of production of graphics and data ...