Data Preparation for Automated Machine Learning hero banner
White Paper

Data Preparation for Automated Machine Learning

The quality of predictive output relies on the quality of input — if you put good in, you’ll get good out. That’s why proper data preparation is such a critical success factor for achieving optimal machine learning results. The iterative process of preparing data for automated machine learning is both an art and a science.

In this White Paper from Jen Underwood of Impact Analytix, she will walk you through the entire machine learning lifecycle and the steps you should take to collect, prepare and understand your data.

In this report, you'll learn:

  • How to avoid overfitting and underfitting
  • The key to detecting leakage in order to find and reduce errors
  • How to improve data quality and engineer features
DataRobot is an indispensable partner helping us maintain our reputation both internally and externally by deploying, monitoring, and governing generative AI responsibly and effectively.
Tom Thomas
Tom Thomas

Vice President of Data & Analytics, FordDirect

The generative AI space is changing quickly, and the flexibility, safety and security of DataRobot helps us stay on the cutting edge with a HIPAA-compliant environment we trust to uphold critical health data protection standards. We’re harnessing innovation for real-world applications, giving us the ability to transform patient care and improve operations and efficiency with confidence
Rosalia Tungaraza
Rosalia Tungaraza

Ph.D, AVP, Artificial Intelligence, Baptist Health South Florida

DataRobot provides us with innovative ways to test new ideas. Given a problem and a dataset, DataRobot allows us to generate multiple prototypes 20% faster. And the process facilitates the learning evolution of our data scientists.
Diego J. Bodas
Diego J. Bodas

Director of Advanced Analytics, MAPFRE ESPAÑA

The value of having a single platform that pulls all the components together can’t be underestimated. Then there’s the combination of the technology and the collaborative DataRobot team. If either one of those wasn’t there, I would have looked elsewhere.
Craig Civil
Craig Civil

Director of Data Science & AI

    Get Your Copy of the White Paper