×

The next frontier of data science is here. Read about it now.

First Name
Last Name
Company Name
!
Thank you!
Error - something went wrong!
   

Feature Generation: The Next Frontier of Data Science

Engineering new, relevant features that move the needle on your predictive models is one of the hardest problems in data science.  Finding and integrating external data to test out those features is, arguably, an even bigger challenge.   

There's so much valuable data out there, but almost no way to find it and use it effectively.

It's time to take feature generation - a subset of feature engineering - from an art to a science by opening up additional data sources to achieve breakthroughs in predictive models. 

This white paper breaks down:  

  • Challenges in feature generation

  • Ways to achieve new breakthroughs in your predictive models by tapping into additional data sources

Previous Article
Clustering — When You Should Use it and Avoid It
Clustering — When You Should Use it and Avoid It

Cluster analysis is an essential tool for data scientists but it shouldn’t be your only one. Discover when ...

Next Article
Support and Coverage – Data Integration Metrics You Should Know
Support and Coverage – Data Integration Metrics You Should Know

Data enrichment is a crucial step in the modeling process that data scientists tend to overlook due to the ...