In this chapter, you learned about time series analysis, M2M communication, and the benefits of time series analysis for commercial banking. We also looked at two useful examples by defining the problem statement and deriving the solution step by step. We also learned about the basic concepts of time series analysis and a few techniques, such as ARIMA.
In the next chapter, we will explore reinforcement learning. Reinforcement learning is an area of machine learning involving algorithms. The application takes an appropriate action to maximize the effectiveness of the outcome in a particular situation. We will also look at how to automate decision-making in banking using reinforcement learning. Exciting, isn't it?
