Summary

This chapter provided you with an overview of what data science is in general. We also learned the different types of machine learning algorithms, including supervised and unsupervised, as well as regression and classification. We had a quick introduction to Python and how to manipulate the main data structures (lists and dictionaries) that will be used in this book.

Then we walked you through what a DataFrame is and how to create one by loading data from different file formats using the famous pandas package. Finally, we learned how to use the sklearn package to train a machine learning model and make predictions with it.

This was just a quick glimpse into the fascinating world of data science. In this book, you will learn much more and discover new techniques for handling data science projects from end to end.

The next chapter will show you how to perform a regression task on a real-world dataset.