Accuracy tells you how many times the ML model was correct overall. Precision is how good the model is at predicting a specific category. Recall tells you how many times the model was able to detect a specific category.

Databases aren’t the only sources of data, modern data pipelines can consume data from various sources.

We explain what SHAP values are, walk you through a real life example, and outline how you can use them to interpret & explain your machine learning models.