By Igor Korolev, DO, PhD, BrainformatikaData science is pretty cool, Its full of many useful tools.
R, and Python, and Excel, Tableau, and SAS, and SQL.
Define the problem, collect the data And youll 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 decisionsData Science needs critical thinking and learning but it can be impactful and rewarding.
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