Aquarium Features

Enables smart selection of data for annotation to reduce overall training time and costs. This feature was mentioned in 13 Aquarium reviews.

Allows for automatic retraining of models with newly annotated data for continuous improvement. This feature was mentioned in 13 Aquarium reviews.

Facilitates the setup of an active learning process tailored to specific AI projects. This feature was mentioned in 13 Aquarium reviews.

Allows users to establish a feedback loop between data annotation and model training. This feature was mentioned in 13 Aquarium reviews.

Provides the ability to identify and address edge cases to enhance model robustness. This feature was mentioned in 12 Aquarium reviews.

As reported in 12 Aquarium reviews. Enables efficient triaging of training data to identify which data points should be labeled next.

Streamlines the data labeling process with tools designed for efficiency and accuracy. 13 reviewers of Aquarium have provided feedback on this feature.

Based on 12 Aquarium reviews. Automates the detection of anomalies and outliers in the training data for correction.

As reported in 12 Aquarium reviews. Offers tools to optimize the selection of data for labeling based on model uncertainty.

Provides actionable insights into data quality, enabling targeted improvements in data labeling. 12 reviewers of Aquarium have provided feedback on this feature.

Delivers in-depth insights into factors impacting model performance and suggests enhancements. 12 reviewers of Aquarium have provided feedback on this feature.

Enables model improvement at the lowest possible cost by focusing on the most impactful data. 12 reviewers of Aquarium have provided feedback on this feature.

Integrates the handling of edge cases into the model training loop for continuous performance enhancement. This feature was mentioned in 12 Aquarium reviews.

As reported in 12 Aquarium reviews. Provides the ability to fine-tune models for increased accuracy and specialization for niche use cases.

Offers advanced tools to analyze label outliers and errors to inform further model training. This feature was mentioned in 12 Aquarium reviews.