gridsearch

A multi-platform desktop application to evaluate and compare LLM models, written in Rust and React.

Solution of the Titanic Kaggle competition

A Reproducible Workflow for Structural and Functional Connectome Ensemble Learning

hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating the results on an independent validation set. hgboost can be applied for classification and regression tasks.

Aims at attributing the big-five personality traits to authors of essays by analyzing their works.

Cross Validation, Grid Search and Random Search for TensorFlow 2 Datasets

🔮 Mastermind puzzle solver using Genetic Algorithm and Grid Search for optimization

A lightweight tool to manage and track your large scale machine leaning experiments

Repo that relates to the Medium blog 'Using Bayesian Optimization to reduce the time spent on hyperparameter tuning'

Data Mining and Machine Learning APS Failure at Scania Trucks Data Set.

Lightweight HyperParameter Optimizer

This project implements famous MAB algorithms and evaluates them on the basis of their performance - EpsilonGreedy, UCB, BetaThompson, LinUCB, LinThompson.

Code for 1th and 2th stage of 2020 NTI ML competition.

Group project: data collection, feature analysis and models to predict secretory signal peptides.

dataclasses enhanced with type validation and serialization

Hyperparameter-Optimization-Tutorial

This project explores ML techniques across classification and regression. It includes penguin species classification, breast cancer prediction, and baseball performance prediction using regularization. After, I will develop an XGBoost model for hotel cancellation prediction, analyzing key booking factors and optimizing performance. (In Progress)

Propositional structure recovery and truth table entropy for hyperparameter search space pruning. Two papers, one library.

Predicting house price