SUMMARY.md

Table of contents

• 🏠 Deep Lake Docs
• List of ML Datasets

🏗️ SETUP

• Installation
• User Authentication
  • Workload Identities (Azure Only)
• Storage and Credentials
  • Storage Options
  • Setting up Deep Lake in Your Cloud
    • Microsoft Azure
      • Configure Azure SSO on Activeloop
      • Provisioning Federated Credentials
      • Enabling CORS
    • Google Cloud
      • Provisioning Federated Credentials
      • Enabling CORS
    • Amazon Web Services
      • Provisioning Role-Based Access
      • Enabling CORS

📚 Examples

• Deep Learning
  • Deep Learning Quickstart
  • Deep Learning Guide
    • 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
  • Deep Learning Tutorials
    • Creating Datasets
      • Creating Complex Datasets
      • Creating Object Detection Datasets
      • Creating Time-Series Datasets
      • Creating Datasets with Sequences
      • Creating Video Datasets
    • Training Models
      • Splitting Datasets for Training
      • Training an Image Classification Model in PyTorch
      • Training Models Using MMDetection
      • Training Models Using PyTorch Lightning
      • Training on AWS SageMaker
      • Training an Object Detection and Segmentation Model in PyTorch
    • Updating Datasets
    • Data Processing Using Parallel Computing
  • Deep Learning Playbooks
    • Querying, Training and Editing Datasets with Data Lineage
    • Evaluating Model Performance
    • Training Reproducibility Using Deep Lake and Weights & Biases
    • Working with Videos
  • Deep Lake Dataloaders
  • API Summary
• RAG
  • RAG Quickstart
  • RAG Tutorials
    • Vector Store Basics
    • Vector Search Options
      • LangChain API
      • Deep Lake Vector Store API
      • Managed Database REST API
    • Customizing Your Vector Store
    • Image Similarity Search
    • Improving Search Accuracy using Deep Memory
  • LangChain Integration
  • LlamaIndex Integration
  • Managed Tensor Database
    • REST API
    • Migrating Datasets to the Tensor Database
  • Deep Memory
    • How it Works
• Tensor Query Language (TQL)
  • TQL Syntax
  • Index for ANN Search
    • Caching and Optimization
  • Sampling Datasets

🔬 Technical Details

• Best Practices
  • Creating Datasets at Scale
  • Training Models at Scale
  • Storage Synchronization and "with" Context
  • Restoring Corrupted Datasets
  • Concurrent Writes
    • Concurrency Using Zookeeper Locks
• Deep Lake Data Format
  • Tensor Relationships
  • Version Control and Querying
• Dataset Visualization
  • Visualizer Integration
• Shuffling in Dataloaders
• How to Contribute