Terminology#
Within Argilla we decided to differentiate our docs using main terminology classes and corresponding sub-classes.
Features#
Specific features that are covered by internal Argilla
functionalities.
Terminology |
Description |
---|---|
Datasets |
Internal |
Metrics |
Argilla |
Queries |
Argilla query functionalities are based on the powerful |
Semantic Search |
This built-in search uses vectors for text and enables Approximate KNN for semantic search on these vectors. |
MLOps Steps#
All steps that we directly or in-directly cover within the MLOps lifecycle
.
Terminology |
Description |
---|---|
๐ท Labelling |
|
๐ช๐ฝ Training |
|
๐จ๐ฝโ๐ป Deploying |
|
๐ Monitoring |
|
NLP Tasks#
Main task categories that we cover within the NLP landscape
.
Terminology |
Description |
---|---|
๐๐ TextClassification |
Assigning predefined category labels to |
๐ด๐ฏ๏ธ TokenClassification |
Assigning predefined category labels to |
๐จ๐ฝ๐ฌ Text2Text |
Generating a |
Techniques#
Best practices and methods that can be applied during Machine Learning
within our eco-system.
Terminology |
Description |
---|---|
๐ผ Basics |
Simple |
๐จ๐ฝโ๐ซ Active Learning |
Actively evaluate |
๐ฎ Weak Supervision |
Use |
๐ Explainability and bias |
|
๐ซ Few-shot classification |
Model and techniques that perform reasonably well using only a |
๐ช Semantic Search |
This built-in search uses vectors for text and enables Approximate KNN for semantic search on these vectors. |