AI Simplified: Cross-Validation
Bill Surrette, a Data Scientist at DataRobot, is back with more helpful insights for DataRobot’s AI Simplified series. This time, Bill focuses on Cross-Validation, an extension of the training, validation, and holdout process. In this video, Bill talks about what to do if you don’t have enough data, or if the data you do have is very noisy.
Missed Bill’s first video? Watch and learn about Training, Validation, and Holdout and why it’s an important key step when developing machine learning models.
In the need for more AI Simplified education? Check out our original AI Simplified video explaining Automated Machine Learning!
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
