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 on 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 l earn 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, 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.
In the next chapter, we will apply...
