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Data Science Design Pattern

Transformations of Individual Variables
Blogs

Data Science Design Pattern #5: Combining Source Variables

Variable selection is perhaps the most challenging activity in the data science lifecycle. Our blog highlights a repeatable approach to variable engineering.

By Drew Clancy, 9 yearsMarch 26, 2014 ago
Transformations of Individual Variables
Blogs

Data Science Design Pattern #4: Transformations of Individual Variables

n this post we describe some common ways to transform individual variables, and explore how doing so may benefit an analysis.

By Drew Clancy, 9 yearsMarch 11, 2014 ago
Transformations of Individual Variables
Blogs

Data Science Design Pattern #3: Handling Null Values

Most data science algorithms do not tolerate nulls (missing values). So, one must do something to eliminate them, before or while analyzing a data set.

By Drew Clancy, 9 yearsMarch 3, 2014 ago
Transformations of Individual Variables
Blogs

Data Science Design Pattern #2: Variable-Width Kernel Smoothing

This data science design pattern blog post focuses on kernel smoothing.

By Drew Clancy, 9 yearsFebruary 19, 2014 ago
Transformations of Individual Variables
Blogs

Data Science Design Pattern #1: Decision Templates

We hope that this blog will become a clearinghouse within the data science community for these data science design patterns, thereby extending the design-pattern tradition in software development and enterprise architecture to data science.

By Drew Clancy, 9 yearsFebruary 14, 2014 ago
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