Supervised ML approaches - Lots of choices

 From Angela Shi

It used to be that analysts would get a set of data, form hypotheses, and then use regression as the model workhorse. Those days are gone and that is a good thing. One of the major advancements from the ML revolution is a providing a broader set of tools to solve data problem. A quick look at the set of supervised learning tools shows the growing complexity of choices. These enhanced tools are especially important as data sets get larger and more complex.  

Are more tools always better? No. The new challenge is learning the unique features of these tools and determining when is the right time to use them. Now, quants must set up models, find data, pick the right tools, and then build the portfolio. The choice set is more complex and requires new skills. A manager's comparative advantage will be associated with making the right tool choice.