Deep Lake
v3.8.2
API Reference
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Deep Lake Docs
Vector Store Quickstart
Deep Learning Quickstart
Storage & Credentials
List of ML Datasets
🏢
High-Performance Features
Introduction
Performant Dataloader
Tensor Query Language (TQL)
Deep Memory
Index for ANN Search
Managed 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
Low-Level API Summary
🔬
Technical Details
Best Practices
Data Layout
Version Control and Querying
Dataset Visualization
Tensor Relationships
Visualizer Integration
Shuffling in dataloaders
How to Contribute
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Deep Learning
The comprehensive guide for Deep Lake in Deep Learning applications.
This Deep Learning Getting Started guide is 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
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Step 4: Customizing Vector Stores
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Step 1: Hello World