Deep Lake is a vector database designed as a data lake for AI, capable of storing and managing vector embeddings, text, images, and videos. It utilizes a tensor format for efficient querying and integration with AI algorithms, making it suitable for similarity search and machine learning workflows. It is open-source and tailored for handling unstructured and multimodal data, with seamless integration with frameworks like PyTorch and TensorFlow.
Deep Lake is an open-source vector database designed as a data lake for AI applications. It is built to store and manage various types of unstructured and multimodal data, such as vector embeddings, text, images, videos, PDFs, and audio files. Deep Lake utilizes a tensor format for efficient querying and seamless integration with AI algorithms and frameworks like PyTorch and TensorFlow. It is suitable for similarity search, machine learning workflows, and connecting data to large language models.
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