Summary

In this chapter, we've seen three different case studies from three different domains using many different statistical and machine learning methods. However, what all of them have in common is that in order to solve them properly, we had to implement a data science mindset. We had to solve problems in an interesting way, obtain data, clean the data, visualize the data, and finally, model the data and evaluate our thinking process.

I do hope that you have found the contents of this book to be interesting and not just the final chapter! I leave it unto you to keep exploring the world of data science. Keep learning Python. Keep learning statistics and probability. Keep your minds open. It is my hope that this book has been a catalyst for you to go out and find even more on the subject.

For further readings past this book, I highly recommend looking into well-known data science books and blogs, such as:

• Dataschool.io—blog by Kevin Markham
• Python for Data Scientists by Packt

If...