v3.1.5

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

v3.1.5

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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Tutorials (w Colab)

Training Models

Workflows for training models using Hub datasets (includes Colab notebooks)

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Last updated 2 years ago

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Training an Image Classification Model in PyTorch

Training an Object Detection and Segmentation Model in PyTorch

Training Models Using MMDetection