Automated Feature Engineering with Feature Discovery in DataRobot
This post was originally part of the DataRobot Community. Visit now to browse discussions and ask questions about DataRobot, AI Platform, data science, and more.
Feature engineering is a critical and time-consuming step for successful machine learning projects. Designing, preparing, generating, and testing impactful features poses significant challenges as enterprises transform their raw data to deployable models.
In this presentation we discuss some common feature engineering techniques in machine learning and DataRobot’s Feature Discovery. This new capability provides for automatic feature engineering for relational datasets with time-awareness. DataRobot Feature Discovery increases quality and productivity when creating and deploying advanced machine learning models for most predictive problems.
More Information
See DataRobot public documentation for Feature discovery.
We will contact you shortly
We’re almost there! These are the next steps:
- Look out for an email from DataRobot with a subject line: Your Subscription Confirmation.
- Click the confirmation link to approve your consent.
- Done! You have now opted to receive communications about DataRobot’s products and services.
Didn’t receive the email? Please make sure to check your spam or junk folders.
-
Harnessing Synthetic Data for Model Training
September 28, 2023· 5 min read -
Introducing the Latest DataRobot Integrations with Google Cloud, Including a New Generative AI Initiative
September 21, 2023· 4 min read -
DataRobot AI Production: Unifying MLOps and LLMOps
September 14, 2023· 7 min read
Latest posts
