MLPrimitives

Getting Started

  • MLPrimitives
  • Overview
    • Why did we create this library?
  • Installation
    • Requirements
    • Install with pip
  • Quickstart
    • Running a Primitive
      • 1. Load a Primitive
      • 2. Load some data
      • 3. Fit the primitive
      • 4. Produce results
    • Tuning a Primitive
      • 1. Load another primitive
      • 2. Split the dataset
      • 3. Fit the new primitive
      • 4. Make predictions
      • 5. Evalute the performance
      • 6. Set new hyperparameter values
      • 7. Re-evaluate the performance
    • What’s Next?
  • Basic Concepts
    • What is a primitive?
    • Types of Primitives
      • Function Primitives
      • Class Primitives
    • Types of Integrations
      • Directly integrable primitives
        • Examples
      • Primitives that require a Python adapter
        • Examples
      • Custom primitives
        • Examples
        • Candidate primitives

Community

  • Community
    • Types of contributions
      • Reporting Issues
        • Request new primitives
        • Request new features
        • Report Bugs
        • Ask for Documentation
      • Write Documentation
      • Contribute code
  • Contributing
    • General Coding Guidelines
    • Unit Testing Guidelines
  • Annotations
    • Creating an annotation for a new primitive
    • Modifying an existing annotation
    • Creating a new version of an existing annotation
  • Adapters
    • Creating a new Adapter
    • Modifying an existing Adapter
  • Custom Primitives
    • Creating a Custom Primitive
    • Modifying a Custom Primitive

Resources

  • API Reference
    • Subpackages
      • mlprimitives.adapters package
        • Submodules
      • mlprimitives.candidates package
        • Subpackages
        • Submodules
      • mlprimitives.custom package
        • Submodules
    • Submodules
      • mlprimitives.cli module
      • mlprimitives.datasets module
      • mlprimitives.evaluation module
      • mlprimitives.utils module
  • Credits
    • Development Lead
    • Contributors
  • History
    • 0.3.5 - 2023-04-14
      • General Imporvements
    • 0.3.4 - 2023-01-24
      • General Imporvements
    • 0.3.3 - 2023-01-20
      • General Imporvements
      • Adapter Improvements
    • 0.3.2 - 2021-11-09
      • Adapter Improvements
    • 0.3.1 - 2021-10-07
      • Adapter Improvements
      • General Imporvements
    • 0.3.0 - 2021-01-09
      • New Primitives
      • Primitive Improvements
      • General Improvements
    • 0.2.5 - 2020-07-29
      • Primitive Improvements
      • Bug Fixes
      • New Primitives
    • 0.2.4 - 2020-01-30
      • New Primitives
      • Primitive Improvements
      • Bug Fixes
    • 0.2.3 - 2019-11-14
      • New Primitives
      • Primitive Improvements
      • Bug Fixes
    • 0.2.2 - 2019-10-08
      • New Primitives
      • Primitive Improvements
    • 0.2.1 - 2019-09-09
      • New Primitives
      • Primitive Improvements
      • Bug Fixes
    • 0.2.0
      • New Features
      • Primitive Improvements
      • Bug Fixes
    • 0.1.10
      • New Features
      • New Pipelines
      • Primitive Improvements
    • 0.1.9
      • New Features
      • New Primitives
      • Primitive Improvements
    • 0.1.8
      • New Primitives
      • New Features
    • 0.1.7
      • General Improvements
      • New Primitives
      • Bug Fixes
    • 0.1.6
      • General Improvements
      • New Primitives
    • 0.1.5
      • New Primitives
      • General Improvements
      • Bug Fixes
    • 0.1.4
      • New Primitives
      • Bug Fixes
    • 0.1.3
      • New Features
    • 0.1.2
      • New Features
      • Bug Fixes
    • 0.1.1
      • New Features
      • Bug Fixes
    • 0.1.0
MLPrimitives
  • Docs »
  • mlprimitives package »
  • mlprimitives.candidates package
  • Edit on GitHub

mlprimitives.candidates package¶

Subpackages¶

  • mlprimitives.candidates.timeseries package
    • Submodules
      • mlprimitives.candidates.timeseries.cyclegan module

Submodules¶

  • mlprimitives.candidates.audio_featurization module
  • mlprimitives.candidates.audio_padding module
  • mlprimitives.candidates.dsp module
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