In this chapter, you got a feel for the broader things we need to make the project work. We saw the steps that are involved in this process by using a text classification example. We saw how to prepare text for machine learning with scikit-learn. We saw Logistic Regression for ML. We also saw a confusion matrix, which is a quick and powerful tool for making sense of results in all machine learning, beyond NLP.
We are just getting started. From here on out, we will dive deeper into each of these steps and see what other methods exist out there. In the next chapter, we will look at some common methods for text cleaning and extraction. Since this is what we will spend up to 80% of our total time on, it's worth the time and energy learning ...
