Scalable in memory compute engine for generic data processing

A plot of the false positive rate versus the true positive rate for a binary classifier.

Predicting qualitative outputs

The most popular Python framework for building machine learning pipelines

A model that performs well on training data, but poorly on test data.

Predicting quantitative outputs

This type of machine learning algorithm is useful on image, textual, and sound data.

Comparing two models on live production data

A portion of labeled data that is not used during model training or tuning.

A model fails to produce good results on training data.

A common technique to reduce model complexity and improve interpretability.

Split your data into 5 segments and hold out each segment once for validation.