v3.2.22

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

API Reference GitHub Slack Service Status Login

API Reference GitHub Slack Service Status Login

v3.2.22

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
List of ML Datasets
Quickstart
Dataset Visualization
Storage & Credentials
API Reference
Enterprise Features
- Querying Datasets
  - Sampling Datasets
- Performant Dataloader
EXAMPLE CODE
Getting Started
Tutorials (w Colab)
Playbooks
API Summary
Technical Details

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Getting Started

The comprehensive guide for learning to use Hub.

PreviousPerformant Dataloader NextStep 1: Hello World

Last updated 1 year ago

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Our Getting Started guide is also available as a Colab Notebook

Step 1: Hello World Step 2: Creating Deep Lake Datasets Step 3: Understanding Compression Step 4: Accessing and Updating Data Step 5: Visualizing Datasets Step 6: Using Activeloop Storage Step 7: Connecting Deep Lake Datasets to ML Frameworks Step 8: Parallel Computing Step 9: Dataset Version Control Step 10: Dataset Filtering