A Julia machine learning framework

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

🔥 A curated list of awesome links related to MySQL / MariaDB / Percona performance tuning

Parallel Hyperparameter Tuning in Python

Time Series Cross-Validation -- an extension for scikit-learn

Open source cross-platform compiler for compute-intensive loops used in AI algorithms, from Microsoft Research

A Magisk module for maximizing the digital audio fidelity by reducing jitters on audio outputs (USB DACs, Bluetooth a2dp, DLNA, etc.)

A friendly python package for Keras Hyperparameters Tuning based only on NumPy and hyperopt.

R package to tune parameters for machine learning(Support Vector Machine, Random Forest, and Xgboost), using bayesian optimization with gaussian process

Streamlined Estimation for Static, Dynamic and Stochastic Treatment Regimes in Longitudinal Data

Easy Hyper Parameter Optimization with mlr and mlrMBO.

A novel Sparse-Coding Based Approach Feature Selection with emphasizing joint l_1,2-norm minimization and the Class-Specific Feature Selection.

Package for machine learning of astronomical objects such as light curves

The distributed statistical machine translation infrastructure consisting of load balancing, text pre/post-processing and translation services. Written in C++ 11 and utilises multicore CPUs by employing multi-threading, allows for secure SSL/TLS communications.

Implementation of a genetic algorithm to determine the parameters of the PID, PI-D, I-PD and PIDA controllers in order to compensate various benchmark processes, which are representative of many industrial applications. In particular, by considering separately a set-point and a load disturbance rejection unit step response the IAE is minimized b…

Swarming behaviour is based on aggregation of simple drones exhibiting basic instinctive reactions to stimuli. However, to achieve overall balanced/interesting behaviour the relative importance of these instincts, as well their internal parameters, must be tuned. In this project, you will learn how to apply Genetic Programming as means of such t…

PyTorch Implementation of Attention Prompt Tuning: Parameter-Efficient Adaptation of Pre-Trained Models for Action Recognition

a library to tune xgboost models

Fractional order proportional derivative controller tuner