Igel vs Aquarium: What are the differences?
Developers describe Igel as "A CLI tool to run machine learning without writing code". It is a delightful machine learning tool that allows to train, test and use models without writing code. On the other hand, Aquarium is detailed as "*Improve Your ML Dataset Quality *". Machine learning models are only as good as the datasets they're trained on It helps ML teams make better models by improving their dataset quality..
Igel and Aquarium belong to "Machine Learning Tools" category of the tech stack.
Some of the features offered by Igel are:
- Supports all state of the art machine learning models (even preview models)
- Supports different data preprocessing methods
- Provides flexibility and data control while writing configurations
On the other hand, Aquarium provides the following key features:
- Upload your dataset to get a health check of its quality, quantity, and diversity. Zoom in and out of your dataset. Uncover distribution biases before you train. Find and fix labeling errors quickly
- Upload model inferences against your labeled datasets and deep dive into its performance. Find where your model is performing well and badly so you can take the best actions to improve it
- With knowledge of your dataset diversity and model performance, it automatically samples the best data to sample to label and retrain on. Your model performance just gets better