There are 0 repository under gridsearch topic.
A multi-platform desktop application to evaluate and compare LLM models, written in Rust and React.
Solution of the Titanic Kaggle competition
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'
A lightweight tool to manage and track your large scale machine leaning experiments
This project implements famous MAB algorithms and evaluates them on the basis of their performance - EpsilonGreedy, UCB, BetaThompson, LinUCB, LinThompson.
Data Mining and Machine Learning APS Failure at Scania Trucks Data Set.
Hyperparameter-Optimization-Tutorial
Code for 1th and 2th stage of 2020 NTI ML competition.
Predicting house price
Comparison and Evaluation of various models in R
Combine grid search with early stopping via cross validation
A model classifying whether a person would survive on Titanic
Analysis of Terry Stops in Seattle
Implementation of various algorithms on scikit-learn's Toy Datasets.
Binary classification, SHAP (Explainable Artificial Intelligence), and Grid Search (for tuning hyperparameters) using EfficientNetV2-B0 on Cat VS Dog dataset.
Prediction of forest cover type in Python.
Build a machine learning model to predict if a credit card application will get approved.
Backpropagation and automatic differentiation, and grid search from scratch.
Bangla Music Mood Detect Pattern Lab Project
Data Analysis of NASA's Kepler mission for exoplanet exploration using Machine Leaning models and Pandas
Breast Cancer Wisconsin Dataset Classifier with Scikit-learn and Streamlit
Cat vs. Dog classification model using traditional ML methods, including data collection, splitting, HOG feature extraction, model training (e.g., SVM, Decision Tree), and fine-tuning via Grid Search.
A summative coursework for CSC8635 Machine Learning with Project
This repository contains the code and data for a comprehensive survival analysis and prediction study conducted on patients with advanced heart failure. The study focused on 299 patients classified as class III/IV heart failure.
An interesting app for predicting the price of houses in Tehran