v3.5.0

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

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

Powered by GitBook

On this page

Was this helpful?

Creating Datasets

Workflows for creating Hub datasets (includes Colab notebooks)

PreviousVector Search Using the Deep Lake Tensor Database NextCreating Complex Datasets

Last updated 1 year ago

Creating Complex Datasets

Creating Object Detection Datasets

Creating Time-Series Datasets

Creating Datasets with Sequences

Creating Video Datasets