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;.
Deep Lake’s primary use cases include Deep Learning Model Training, Data Lineage and Version Control, Data Querying, and Analytics, Data Inspection and Quality Control. We took NumPy arrays as a fundamental block and implemented version control, streaming dataloaders, visualization engine from scratch. 7.
Deep Lake’s primary use cases include Deep Learning Model Training, Data Lineage and Version Control, Data Querying, and Analytics, Data Inspection and Quality Control. We took NumPy arrays as a fundamental block and implemented version control, streaming dataloaders, visualization engine from scratch. 7.
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