Documentation for the Health Intelligence Machine Learning toolbox hi-ml

This toolbox helps to simplify and streamline work on deep learning models for healthcare and life sciences, by providing tested components (data loaders, pre-processing), deep learning models, and cloud integration tools.

The hi-ml toolbox provides

• Functionality to easily run Python code in Azure Machine Learning services

• Low-level and high-level building blocks for Machine Learning / AI researchers and practitioners.

Working with Azure

• First steps: How to run your Python code in the cloud
• Connecting to Azure
• Datasets
• Hyperparameter Search via Hyperdrive
• Using Cheap Low Priority VMs
• Commandline tools
• Downloading from/ uploading to Azure ML
• Examples

Machine Learning

• Logging metrics when training models in AzureML
• Performance Diagnostics

Developers

• Notes for developers
• Contributing to this toolbox

Guidelines

• Loading Images
• Results
• Whole Slide Images

API

• health_azure Package
  • Functions
  • Classes
• health_ml.utils Package
  • Functions
  • Classes

Indices and tables

• Index

• Module Index

• Search Page