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

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

Lightweight HyperParameter Optimizer

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

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

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.

Hyperparameter-Optimization-Tutorial

Predicting house price

Build a machine learning model to predict if a credit card application will get approved.

Binary classification, SHAP (Explainable Artificial Intelligence), and Grid Search (for tuning hyperparameters) using EfficientNetV2-B0 on Cat VS Dog dataset.

Implementation of various algorithms on scikit-learn's Toy Datasets.

Prediction of forest cover type in Python.