Deep Lake, a Lakehouse for Deep Learning: Machine Learning Use Cases

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Researchers introduce Deep Lake, an open-source lakehouse for deep learning, optimizing complex data storage and streaming for deep learning frameworks.

Authors: Sasun Hambardzumyan, Activeloop, Mountain View, CA, USA; Abhinav Tuli, Activeloop, Mountain View, CA, USA; Levon Ghukasyan, Activeloop, Mountain View, CA, USA; Fariz Rahman, Activeloop, Mountain View, CA, USA;.

In this section, we review the applications of Deep Lake. A typical scenario in a Deep Learning application starts with A raw set of files that is collected on an object storage bucket. It might include images, videos, and other types of multimedia data in their native formats such as JPEG, PNG or MP4. Any associated metadata and labels stored on a relational database.

In this section, we review the applications of Deep Lake. A typical scenario in a Deep Learning application starts with A raw set of files that is collected on an object storage bucket. It might include images, videos, and other types of multimedia data in their native formats such as JPEG, PNG or MP4. Any associated metadata and labels stored on a relational database.

 

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