Background problem

Automation is taking over in almost every sector, and the financial market is no exception. Creating automated algorithmic trading models will provide for a faster and more accurate analysis of stocks before purchase. Multiple indicators can be analyzed at a speed that humans are incapable of. Also, in trading, it is dangerous to operate with emotions. Machine learning models can solve that problem. There is also a reduction in transaction costs, as there is no need for continuous supervision.

In this tutorial, you will learn how to combine reinforcement learning with time series modeling, in order to predict the prices of stocks, based on real-life data.

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