データサイエンス100本ノック（構造化データ加工編）

In-context Bayesian Optimization

Python library to use packages in OptunaHub

Frontend of OptunaHub Registry

The registry of the OptunaHub packages

Enumerate derivative structures

Apache Log4j 2 is a versatile, feature-rich, efficient logging API and backend for Java.

A hyperparameter optimization framework

Extended functionalities for Optuna in combination with third-party libraries.

Distributed hyperparameter optimization made easy

Benchmark framework to easily compare Bayesian optimization methods on real machine learning tasks

[NOT MAINTAINED] Cython accelerated fANOVA implementation for Optuna.

Real-time Web Dashboard for Optuna.

scikit-learn: machine learning in Python

Synchronize your working directory efficiently to a remote place without committing the changes.

Code associated with paper "High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization"

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

run black on documentation code snippets

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

Parallel computing with task scheduling

Benchmark datasets, data loaders, and evaluators for graph machine learning

Python library for CMA Evolution Strategy.

A black-box optimization benchmark tool

Optuna + LightGBM = OptGBM