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v2.1.0

Contents:

  • Installation
  • Tutorial
    • First Optimization
    • Advanced Configurations
    • Saving/Resuming Study with RDB Backend
    • Distributed Optimization
    • Command-Line Interface
    • User Attributes
    • Pruning Unpromising Trials
    • User-Defined Sampler
  • API Reference
  • FAQ
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Tutorial¶

Below tutorials cover the basic concepts and usage of Optuna. The order we assume is as follows:

  • First Optimization

  • Advanced Configurations

  • Saving/Resuming Study with RDB Backend

  • Distributed Optimization

  • Command-Line Interface

  • User Attributes

  • Pruning Unpromising Trials

  • User-Defined Sampler

Other Resources:

  • Examples: More examples including how to use Optuna with popular libraries for machine learning and deep learning.

First Optimization

First Optimization¶

Advanced Configurations

Advanced Configurations¶

Saving/Resuming Study with RDB Backend

Saving/Resuming Study with RDB Backend¶

Distributed Optimization

Distributed Optimization¶

Command-Line Interface

Command-Line Interface¶

User Attributes

User Attributes¶

Pruning Unpromising Trials

Pruning Unpromising Trials¶

User-Defined Sampler

User-Defined Sampler¶

Download all examples in Python source code: tutorial_python.zip

Download all examples in Jupyter notebooks: tutorial_jupyter.zip

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