Optimize your datasets for ML Goodbye, boilerplate code

Better data for your team, at scale

Features

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    Load Data from Anywhere

    Hub works locally, on Google Cloud, MinIO, AWS, Azure as well as Activeloop storage (no servers needed). Load data (even from Kaggle!) and directly stream datasets from cold storage to ML workflows. It's that fast.
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    Dataset Version Control

    Modify dataset elements across different versions and seamlessly switch between them. Hub's intuitive Python API works with datasets of any size and overcomes the limitations of file-based version control.
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    Transformations at Scale

    Quickly modify, update, or resample your datasets in order to find the optimal dataset for your models. Scale to hundreds of machines with one line of code.
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    Scalable Model Training

    Stream your dataset to PyTorch or TensorFlow with one line of code. Train in a distributed fashion with Ray to efficiently utilize your compute resources.
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    Team and Access Management

    Keep your datasets private, share them with your organization or anyone on the web. Have multiple data scientists working on the same data? We can handle that, too.
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    Dataset Querying

    Easily filter, subset or query terabyte-scale datasets to generate instant insights and uncover opportunities for dataset optimization.