ClearML Hyper-Datasets

Build Data-Centric AI workflows

Make the most out of your unstructured-data using queryable datasets

Hyper-Dataset workflow

Leverage unstructured data

Explore

Organize, explore, and analyze a searchable catalog of your datasets with fully searchable version trees.

Query

Slice, split, and sort by meta-data matching, allowing to oversample and debias datasets on-the-fly.

Store your queries in a fully reproducible entity, DataView, in conjunction with your code for full provenance and model reproducibility.

Visualize

Gain insights into your data using the meta-data search capabilities. Visualize any data and edit meta-data directly from the UI or programmatically and instantly view object distribution statistics for any dataset version for additional visibility.

Orchestrate

Decouple training and testing code, enabling users to test & validate models directly from the web UI & use a programmatic interface available through a flexible query mechanism with any data distribution and on multiple weighted queries.

Data-Centric model development

Learn how Neural Guard developed a methodology to build datasets for DL models that optimize ROI and TTM to increase competitiveness in their market.

Review Neural Guard’s process and how ClearML Hyper-Datasets granted all needed functionality in a single, highly integrated MLOps toolchain to build specialized pipelines and connect to both research and production environments.
Case study

Hyper-Datasets and beyond

ClearML Hyper-Datasets integrates seamlessly with ClearML Experiment and ClearML Orchestrate, leveraging end-to-end cross-department visibility in your research, development, and production.

ClearML DataOps

ClearML Remote

ClearML Hyper-Datasets

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