Summary
This concludes our long journey into the principles of data science. In the last 300 odd pages, we looked at different techniques in probability, statistics, and machine learning to answer the most difficult questions out there. I would like to personally congratulate you for making it through this book. I hope that it proved useful and inspired you to learn even more!
This isn't everything I need to know?
Nope! There is only so much I can fit into a principles level book. There is still so much to learn.
Where can I learn more?
I recommend going to find open source data challenges (https://www.kaggle.com/ is a good source) for this. I'd also recommend seeking out, and trying and solving your own problems at home!
When do I get to call myself a data scientist?
When you begin cultivating actionable insights from datasets, both large and small, that companies and people can use, then you have the honor of calling yourself a true data scientist.
