Popular GitHub Repositories for Random Search

Python library to easily log experiments and parallelize hyperparameter search for neural networks

Square Attack: a query-efficient black-box adversarial attack via random search [ECCV 2020]

Hyperparameter optimization algorithms for use in the MLJ machine learning framework

Tuning the Parameters of Heuristic Optimizers (Meta-Optimization / Hyper-Parameter Optimization)

Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks

Different hyperparameter optimization methods to get best performance for your Machine Learning Models

A simple JAX-based implementation of random search for locomotion tasks using MuJoCo XLA (MJX).

Demonstrates how to utilize XGBoost for traffic forecasting using data gathered from IoT sensors, highlighting its efficiency in processing complex datasets and delivering accurate predictions.

Brute Force Architecture Search

This package is an automatic machine learning module whose function is to optimize the hyper-parameters of an automatic learning model.

An AutoRecSys Library built around LensKit. Performs automatic algorithm selection, hyperparameter optimzation and ensembling on LensKit models.

We have developed a regression model aiming to predict the prices of used cars in India using the attributes from the dataset.

Using Scikit-Learn to optimize some of the hyperparameters of Classic ML Models

Perform Neural Architecture Search to find the optimal ANN architecture for classification on two datasets: Splice and Human Activity Recognition