gridsearch
There are 68 repositories under gridsearch topic.
dezoito/ollama-grid-search
A multi-platform desktop application to evaluate and compare LLM models, written in Rust and React.
ahmedbesbes/How-to-score-0.8134-in-Titanic-Kaggle-Challenge
Solution of the Titanic Kaggle competition
dPys/PyNets
A Reproducible Workflow for Structural and Functional Connectome Ensemble Learning
erdogant/hgboost
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.
desaichirayu/Personality-Attribution-using-Natural-Language-Processing
Aims at attributing the big-five personality traits to authors of essays by analyzing their works.
franneck94/TensorCross
Cross Validation, Grid Search and Random Search for TensorFlow 2 Datasets
NongMindHouse/MasterNongMind
🔮 Mastermind puzzle solver using Genetic Algorithm and Grid Search for optimization
MBKraus/Hyperopt
Repo that relates to the Medium blog 'Using Bayesian Optimization to reduce the time spent on hyperparameter tuning'
matthieu637/lhpo
Lightweight HyperParameter Optimizer
dashifyML/dashifyML
A lightweight tool to manage and track your large scale machine leaning experiments
abhinavcreed13/Multi-armed-bandits-MAB
This project implements famous MAB algorithms and evaluates them on the basis of their performance - EpsilonGreedy, UCB, BetaThompson, LinUCB, LinThompson.
jvirico/scania-truck-failure-prediction
Data Mining and Machine Learning APS Failure at Scania Trucks Data Set.
aggarwalpiush/Hyperparameter-Optimization-Tutorial
Hyperparameter-Optimization-Tutorial
Egoluback/nti_ml_20-21
Code for 1th and 2th stage of 2020 NTI ML competition.
Katerinafomkina/House-Predicting-Advanced-Regression-Techniques
Predicting house price
dikshap07/MidTerm_Project516
Comparison and Evaluation of various models in R
dmolitor/xgboost-gridsearch
Combine grid search with early stopping via cross validation
Egoluback/titanic_kaggle
A model classifying whether a person would survive on Titanic
melodygr/Classification_Project
Analysis of Terry Stops in Seattle
mukeshmk/toy-datasets
Implementation of various algorithms on scikit-learn's Toy Datasets.
OmidGhadami95/EfficientNetV2_CatVSDog
Binary classification, SHAP (Explainable Artificial Intelligence), and Grid Search (for tuning hyperparameters) using EfficientNetV2-B0 on Cat VS Dog dataset.
sebastienmeyer2/cover-type-prediction
Prediction of forest cover type in Python.
shreeratn/Predicting-Credit-Card-Approval
Build a machine learning model to predict if a credit card application will get approved.
soran-ghaderi/backpropagation
Backpropagation and automatic differentiation, and grid search from scratch.
Turjo7/Bangla-Music-Mood
Bangla Music Mood Detect Pattern Lab Project
ZenAcar/Exoplanet-Exploration-with-MachineLearning
Data Analysis of NASA's Kepler mission for exoplanet exploration using Machine Leaning models and Pandas
aysenurcftc/breast_cancer_streamlit
Breast Cancer Wisconsin Dataset Classifier with Scikit-learn and Streamlit
sebastienmeyer2/molecule-type-prediction
Prediction of molecule type in Python.
tharangachaminda/banknotes_analysis
Python project for Banknotes Analysis.
abisiv05/assignments
Assignments for the course Applied Machine Learning at NMBU.
Denis-Mukhanov/spark-home-value-prediction
Yandex Practicum Data Science project
hugohiraoka/Personal_Loan_Campaign_Customer_Prediction
Logistic Regression and Decision Tree models to predict Customers purchasing a Loan from the bank.
mzaid295/Cats-and-Dog-Classification-Using-Support-Vector-Machine---HOG-Features
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.
Wayneotc/Heart-Failure
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.
Wayneotc/Telco-Customer-churn
This project aims to predict customer churn using machine learning techniques. By understanding the factors that contribute to churn, businesses can take proactive measures to retain customers and maximize their customer base. The project focuses on developing a predictive model using machine learning algorithms to forecast customer churn.