By Igor Korolev, DO, PhD, Brainformatika
Data science is pretty cool,
It's full of many useful tools.
R, and Python, and Excel,
Tableau, and SAS, and SQL.
Define the problem, collect the data
And you'll discover insights later.
Extract, transform, load, and clean
Visualize on your big screen.
Follow the domain expert leads,
Create the features data needs.
Choose machine learning algorithms to run
Regression, random forests,
Neural networks for ultimate fun.
Split the data into train and test
Find parameters which work best
Evaluate with AUC, recall, and precision
Present insights that help with decisions
Data Science needs critical thinking and learning
but it can be impactful and rewarding.