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v2.5.0

Contents:

  • Installation
  • Tutorial
    • Key Features
      • Lightweight, versatile, and platform agnostic architecture
      • Pythonic Search Space
      • Efficient Optimization Algorithms
      • Easy Parallelization
      • Quick Visualization for Hyperparameter Optimization Analysis
    • Recipes
      • Saving/Resuming Study with RDB Backend
      • User Attributes
      • Command-Line Interface
      • User-Defined Sampler
      • Callback for Study.optimize
      • Specify Hyperparameters Manually
  • API Reference
  • FAQ
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Tutorial¶

If you are new to Optuna or want a general introduction, we highly recommend the below video.




Key Features¶

Showcases Optuna’s Key Features.

Lightweight, versatile, and platform agnostic architecture

Lightweight, versatile, and platform agnostic architecture¶

Pythonic Search Space

Pythonic Search Space¶

Efficient Optimization Algorithms

Efficient Optimization Algorithms¶

Easy Parallelization

Easy Parallelization¶

Quick Visualization for Hyperparameter Optimization Analysis

Quick Visualization for Hyperparameter Optimization Analysis¶

Recipes¶

Showcases the recipes that might help you using Optuna with comfort.

Saving/Resuming Study with RDB Backend

Saving/Resuming Study with RDB Backend¶

User Attributes

User Attributes¶

Command-Line Interface

Command-Line Interface¶

User-Defined Sampler

User-Defined Sampler¶

Callback for Study.optimize

Callback for Study.optimize¶

Specify Hyperparameters Manually

Specify Hyperparameters Manually¶

Download all examples in Python source code: tutorial_python.zip

Download all examples in Jupyter notebooks: tutorial_jupyter.zip

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