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v3.0.0-b1

Contents:

  • Installation
  • Tutorial
    • Key Features
      • 1. Lightweight, versatile, and platform agnostic architecture
      • 2. Pythonic Search Space
      • 3. Efficient Optimization Algorithms
      • 4. Easy Parallelization
      • 5. Quick Visualization for Hyperparameter Optimization Analysis
    • Recipes
      • Saving/Resuming Study with RDB Backend
      • Multi-objective Optimization with Optuna
      • User Attributes
      • Command-Line Interface
      • User-Defined Sampler
      • User-Defined Pruner
      • Callback for Study.optimize
      • Specify Hyperparameters Manually
      • Ask-and-Tell Interface
      • Re-use the best trial
  • API Reference
  • FAQ
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  • Tutorial
  • Edit on GitHub

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.

1. Lightweight, versatile, and platform agnostic architecture

1. Lightweight, versatile, and platform agnostic architecture

2. Pythonic Search Space

2. Pythonic Search Space

3. Efficient Optimization Algorithms

3. Efficient Optimization Algorithms

4. Easy Parallelization

4. Easy Parallelization

5. Quick Visualization for Hyperparameter Optimization Analysis

5. 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

Multi-objective Optimization with Optuna

Multi-objective Optimization with Optuna

User Attributes

User Attributes

Command-Line Interface

Command-Line Interface

User-Defined Sampler

User-Defined Sampler

User-Defined Pruner

User-Defined Pruner

Callback for Study.optimize

Callback for Study.optimize

Specify Hyperparameters Manually

Specify Hyperparameters Manually

Ask-and-Tell Interface

Ask-and-Tell Interface

Re-use the best trial

Re-use the best trial

Download all examples in Python source code: tutorial_python.zip

Download all examples in Jupyter notebooks: tutorial_jupyter.zip

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