e.g. The is_fraud training set contains a set of features __ (amt_spent, avg_transaction_amt, number_of_fraud, etc.) and labels.
Models: Programs that can make predictions on a previously unseen dataset, after being trained with training sets.
e.g. The user_fraud_random_forest model is a classifier, predicting whether a user committed fraud.
****Providers: Data infrastructure used for storage or computation.
Users: Individual data scientists who create, share, or reuse features and models.
Resource Pages: Features, Sources, Labels, Training Sets
Resources pages generally have the same format. They display a list of that resource type, along with descriptions.
Sources page of the Feature Registry
The feature page has additional columns, namely "type" and "default variant".
Feature page of the Feature Registry
Click on the arrow next to a source name to see a list of variants of that resource.
Dropdown view of variants on the user_transaction_count, 30d and 7d
Next, click on a variant (or the resource name for the default variant) to pull up more details, including the description, owner, provider, data type, status, source, entity, and columns. Some fields link to more information. Change the variant by using the small dropdown menu on the top-right.
Detailed view of the user_transaction_count feature
Metrics, namely throughput, latency, and errors for that variant are displayed for features and training sets.
Metrics view of a feature variant
The entities page is similar to other resource types, except that there are 3 tabs ("Features", "Labels", "Training Sets"). The features, labels, and training sets corresponding to that entity are shown under these tabs, with the ability to select variants and see detailed views.
Entities page of the Feature Registry
The providers page shows all providers, with the corresponding name, description, type, and software.
Providers page of the Feature Registry
Click on the providers to pull up the sources, features, labels, and training sets originating from that provider.
Detailed view of a single provider
The models page shows all model names, with the corresponding description. Model names are provided by the user at serving time. Featureform tracks which features and training sets are associated with which model names. However, models are not stored.
Models page of the Feature Registry
The users page show all users' names. Click on a user to view features, labels, training sets, and sources associated with that user.