# Intro to Aquarium {% embed url="" %} ## What is Aquarium? **Aquarium is an ML data operations platform that helps teams find issues, validate fixes, and add the right data to improve their machine learning datasets.** ML models are defined by a combination of code and the data. While there's a lot of great tools for debugging and understanding code, there's not a lot of tooling for debugging and understanding the actual data.\ \ Our interactive views and collaborative platform allows your teams to work more efficiently on data-centric workflows with the goal of: * Speeding up your ML workflows * Saving engineering time * Reducing operational risk ## When Should I Use Aquarium? **You should use Aquarium when you're trying to build or improve an ML model.** Most gains to model performance come from improving datasets rather than model code. And as a result, it's hard to make significant gains in the code without large time investments. Thats where we come in! Aquarium can improve on your team's ML tasks like: **Assessing Data Quality** * Find labeling errors and subsets of your data that have interesting/problematic patterns * Easy to use interface encourages other members in the process to get involved which leads to freeing up your ML engineers time **Comparing Model Performance** * Diagnose the causes of critical model errors across multiple versions of your model * Compare multiple models with regression tests to ensure each iteration of your model is truly an improvement **Collecting Relevant Data** * Quickly identify the highest value data to collect that improves the model performance * Reduce manual time spent trawling through unlabeled data to figure out what to label next Teams have seen up to a 25% increase in model performance in a single cycle of dataset iteration with up to 8x less time spent than in their previous workflow! ## What Does Aquarium Support? **Aquarium supports the following ML tasks:** * Classification * 2D Object Detection * 3D Object Detection * Semantic Segmentation {% hint style="info" %} If your team has a nuanced task or you work with a particular kind of data, feel free to reach out to our team [here](https://www.aquariumlearning.com/contact)! {% endhint %} ## How Do I Get Started With Aquarium? We provide a variety of quickstart guides to help you get familiar with our data upload process, and we also provide documentation around how to complete certain ML tasks and workflows. {% content-ref url="quickstart-guides" %} [quickstart-guides](https://legacy-docs.aquariumlearning.com/aquarium/getting-started/quickstart-guides) {% endcontent-ref %} In addition we have detailed documentation on how to upload different kinds of data listed here: {% content-ref url="../common-workflows/assess-data-quality" %} [assess-data-quality](https://legacy-docs.aquariumlearning.com/aquarium/common-workflows/assess-data-quality) {% endcontent-ref %} For further questions or scheduling time for a demo or discussion, you can reach out to Aquarium [here](https://www.aquariumlearning.com/contact)! ## Further reading * Our website: * Our Hacker News launch post: * Software 2.0: