W4- Machine Learning Data Lifecycle in Production

Question 1

How is semi-supervised labeling done?

Semi-supervised Learning 02:08

Answer 1

With Semi-supervised labeling, you start with a relatively small dataset that’s been labeled by humans. Then you’ll combine that labeled data with a large amount of unlabeled data, where you’ll infer the labels for the unlabeled data by looking at how the different human labeled classes are clustered or structured within the feature space. Then you’ll train your model using the combination of the two datasets.

Label propagation itself is considered transductive learning, meaning that we’re mapping from the examples themselves without learning a function for the mapping.

Question 2

The intelligent sampling of ____ labeling method, selects the unlabeled points that would bring the most predictive value to your model.

Active Learning 00:04

Answer 2

Active learning