Data integrity involves looking at data to ensure data is not only correct, but also applied to accurate context, has been properly collected, stored and more.
Supervised learning is an approach to machine learning that uses labeled data sets to train algorithms in order to properly classify data and predict outcomes.
R is a programming language that provides access to a variety of statistical and graphical techniques while producing plots. R is widely used in data science.
Feature importance involves calculating a score for all input features in a machine learning model to determine which ones are the most important. Here’s how to do it.
Python is a general-purpose, object-oriented programming language that’s popular in data science thanks to its rich libraries offering deep learning capabilities.
