optuna and optuna-examples
The examples repository serves as supplementary documentation and use-case demonstrations for the main hyperparameter optimization framework, making them complements that are typically used together rather than alternatives.
About optuna
optuna/optuna
A hyperparameter optimization framework
This tool helps machine learning practitioners fine-tune their models. You define your model's parameters and a performance metric, and Optuna automatically runs many experiments to find the best combination of settings. This results in highly optimized models without extensive manual trial and error.
About optuna-examples
optuna/optuna-examples
Examples for https://github.com/optuna/optuna
This project provides practical, ready-to-use code examples for optimizing various parameters in your models and algorithms. It takes in your model's objective function and returns the best combination of parameters to achieve desired outcomes, such as higher accuracy or faster performance. Machine learning engineers, data scientists, and researchers will find this useful for fine-tuning their models and experiments across different frameworks.
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