In this chapter, we took a look at the stock market. We learned how to formulate a trading strategy using machine learning. We built the first strategy using a support vector regression and the second using dynamic time warping.

There is no doubt that the material of this chapter could fill a book in itself. Many of the most important components of a trading strategy, we didn't even cover. These include portfolio construction, risk mitigation, and money management. These are fundamental to any real strategy—arguably more important than trade signals.

Hopefully, this will serve as a jumping point for your own explorations. However, again I caution you that "beating the market" is a nearly impossible game. It is one in which you are competing against the brightest minds in the world. If you do decide to try, I wish you the best of luck. Just remember that I warned you if it doesn't turn out like you hoped!

In the next chapter we will examine how to build an image similarity engine.