Summary

In this chapter, we have seen how to develop an ML project to predict whether a customer is likely to cancel their subscription or not, and then used it to develop a real-life predictive model. We have developed predictive models using LR, SVMs, DTs, and Random Forest. We have also analyzed what types of customer data are typically used to do preliminary analysis of the data. Finally, we have seen how to choose which model to use for a production-ready environment.

In the next chapter, we will see how to develop a real-life project that collects historical and live Bitcoin data and predicts the price for an upcoming week, month, and so on. In addition to this, we will see how to generate a simple signal for online cryptocurrency trading.