A guide to the data science life cycle
The six stages of the data science life cycle — define, collect, explore, model, evaluate, deploy — and why the process is iterative, not linear.
2 articles
The six stages of the data science life cycle — define, collect, explore, model, evaluate, deploy — and why the process is iterative, not linear.
Correlation measures the linear relationship between two variables and is one building block of multivariate analysis. How they relate, and the caveats.