tuning-parameters

A Julia machine learning framework

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

Hyperparameter optimization for PyTorch.

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

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

Parallel Hyperparameter Tuning in Python

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

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.

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

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 tuning, and attempt to achieve a series of non-trivial swarm-level behaviours.

Machine Learning Hyper-parameter Tuning processes

Tuning Monte Carlo generators with machine learning.

Optimizing-Hyperparameters-Using-Grid-Search-Deep-Learning

Fractional order proportional derivative controller tuner

XTune: A custom python wrapper for XGBoost and LightGBM with numerous utility functions to prevent silly gotchas and save time!

Implementation of Deep-learning techniques in pytorch

a library to tune xgboost models

Hyper-parameter + encoding + architecture grid/random search for keras

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

In this repository, a regression analysis is conducted using different machine learning and deep learning models. The study is led in order to choose the most suitable model by looking at different characteristics (models tuning, features scaling, etc).

MATLAB code for tuning a PID controller using Genetic Algorithm (GA)

⚛️ Deep Learning Specialization by deeplearning.ai

Support Vector machine In detail: /implementation in Python&R/and tuning SVM parameters

Using P, PI, PD, PID Controllers to Control a Simulated Drone