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v3.6.1

v3.9.16 v3.9.0 v3.8.27 v3.8.19 v3.8.16 v3.8.2 v3.8.0 v3.7.2 v3.7.1 v3.7.0 v3.6.18 v3.6.10 v3.6.8 v3.6.3 v3.6.2 v3.6.1 v3.6.0 v3.5.0 v3.4.0 v3.2.22 v3.2.21 v3.2.9 v3.2.0 v3.1.5 v3.1.1 v3.1.0 v3.0.16 v3.0.10 v3.0.0

v3.6.1

v3.9.16 v3.9.0 v3.8.27 v3.8.19 v3.8.16 v3.8.2 v3.8.0 v3.7.2 v3.7.1 v3.7.0 v3.6.18 v3.6.10 v3.6.8 v3.6.3 v3.6.2 v3.6.1 v3.6.0 v3.5.0 v3.4.0 v3.2.22 v3.2.21 v3.2.9 v3.2.0 v3.1.5 v3.1.1 v3.1.0 v3.0.16 v3.0.10 v3.0.0

Deep Lake Docs
Vector Store Quickstart
Deep Learning Quickstart
Storage & Credentials
List of ML Datasets
API Reference
🏢Enterprise Features
- Compute Engine
  - Tensor Query Language (TQL)
    TQL Syntax
    Sampling Datasets
  - Performant Dataloader
- Tensor Database
  - REST API
  - Migrating Datasets to the Tensor Database
📚EXAMPLE CODE
Getting Started
- Vector Store
- Deep Learning
Tutorials (w Colab)
Playbooks
API Summary
🔬Technical Details

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Comprehensive Guide for Getting Started with Deep Lake's Primary Use Cases:
Vector Store use cases are implemented using a simpler API designed for Vector Search applications
Deep Learning use cases are implemented using a the low-level Deep Lake API that offers maximum customizability

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Getting Started

Comprehensive guides for getting started with Deep Lake

PreviousMigrating Datasets to the Tensor Database NextVector Store

Last updated 1 year ago

Was this helpful?

Comprehensive Guide for Getting Started with Deep Lake's Primary Use Cases:

Vector Store use cases are implemented using a simpler API designed for Vector Search applications

Deep Learning use cases are implemented using a the low-level Deep Lake API that offers maximum customizability