v3.1.0

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

v3.1.0

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
- Storage Options
- Managed Credentials
  Enabling CORS
  Provisioning Role-Based Access
API Reference
Enterprise Features
- Querying Datasets
  - Sampling Datasets
- Performant Dataloader
EXAMPLE CODE
Getting Started
Tutorials (w Colab)
Playbooks
API Summary
How Deep Lake Works

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Getting Started

The comprehensive guide for learning to use Hub.

PreviousPerformant Dataloader NextStep 1: Hello World

Last updated 2 years ago

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 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