Remove Azure Remove Cloud Computing Remove Cross Validation
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Meet the finalists of the Pushback to the Future Challenge

DrivenData Labs

Several additional approaches were attempted but deprioritized or entirely eliminated from the final workflow due to lack of positive impact on the validation MAE. What are some other things you tried that didn't necessarily make it into the final workflow?

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Must-Have Skills for a Machine Learning Engineer

Pickl AI

Familiarity with cloud computing tools supports scalable model deployment. Key concepts include: Cross-validation Cross-validation splits the data into multiple subsets and trains the model on different combinations, ensuring that the evaluation is robust and the model doesn’t overfit to a specific dataset.