BotLibre VS optuna

Compare BotLibre vs optuna and see what are their differences.

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BotLibre optuna
1 32
565 9,471
1.4% 3.0%
7.2 9.9
3 months ago 2 days ago
Java Python
Eclipse Public License 1.0 GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

BotLibre

Posts with mentions or reviews of BotLibre. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-03-03.

optuna

Posts with mentions or reviews of optuna. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-09.

What are some alternatives?

When comparing BotLibre and optuna you can also consider the following projects:

Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

hyperopt - Distributed Asynchronous Hyperparameter Optimization in Python

rl-baselines3-zoo - A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

mljar-supervised - Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

pyGAM - [HELP REQUESTED] Generalized Additive Models in Python

pg_plan_advsr - PostgreSQL extension for automated execution plan tuning

SMAC3 - SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

Empirical_Study_of_Ensemble_Learning_Methods - Training ensemble machine learning classifiers, with flexible templates for repeated cross-validation and parameter tuning

highway - Performance-portable, length-agnostic SIMD with runtime dispatch

optuna-examples - Examples for https://github.com/optuna/optuna

xsimd - C++ wrappers for SIMD intrinsics and parallelized, optimized mathematical functions (SSE, AVX, AVX512, NEON, SVE))