If you had fun doodling and building (and running the model to recognize doodling) on your mobile devices in the last chapter, you'll possibly also have fun when you make money in the stock market, or get serious when you don't. On the one hand, stock prices are time-series data, a sequence of discrete-time data, and the best deep learning method to deal with time series data is RNN, which we have used in the last two chapters. Aurélien Géron, in his best seller, Hands-On Machine Learning with Scikit-Learn and TensorFlow, suggested using RNN to "analyze time series data such as stock prices, and tell you when to buy or sell." On the other hand, others think the past performance of a stock cannot predict its future returns, and a randomly selected portfolio would do just as well as one carefully selected by experts...