First, let’s start with the “80/20” of data science…
Generally speaking, we can break down applied machine learning into the following chunks:
This data science primer will cover exploratory analysis, data cleaning, feature engineering, algorithm selection, and model training. As you can see, those chunks make up 80% of the pie. They also set the foundation for more advanced techniques.
In this first chapter, you’ll see how these moving pieces fit together. Therefore, we suggest the following two tips to making the most out of this primer:
Tip #1 - Don’t sweat the details (for now).
We’ve seen students master this subject 2X faster by first understanding how all the pieces fit together… and then diving deeper. Our trainings all follow this “top-down” approach.
Tip #2 - Don’t worry about coding (yet).
Again, it’s easy to get lost in the weeds at the beginning… so our goal is to see the forest instead of the trees. Don’t worry - We’ll get to the code later.