catboost-classifier
There are 78 repositories under catboost-classifier topic.
edaaydinea/OP1-Prediction-of-the-Different-Progressive-Levels-of-Alzheimer-s-Disease
This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD).
edaaydinea/OP2-Prediction-of-the-Different-Progressive-Levels-of-Alzheimer-s-Disease-with-MRI-data
This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD) with MRI data.
Egoluback/Toxic_Detector
ML-bot that detects toxicity in russian texts.
yoraghav/Automated_Hangman
Uses letter frequency and catboost classifier model in synchronous for guessing letters in hangman game instance. The model performance is evaluated on both seen words in the dictionary and words out of the dictionary.
BMSTU-team/vector_ECG_team_project
Командный проект по Векторной электрокардиографии
sachin17git/Malware-detection-ML
Android malware detection using machine learning.
salim-benhamadi/landslide-prevention-and-innovation-challenge
Classifying if a landslide occured or not
Prashant-Tiwari26/Multimodal-Sentiment-Analysis-using-Text-and-Images
Multimodal Sentiment Analysis using Text and Image Data on twitter dataset
himarygr/disease-prediction-ml-model-app
A model on the streamlit framework predicts disease and makes a treatment recommendation
k-loki/Mars-spectrometry-14th-place-solution
This is my final solution to the Mars-spectrometry challenge by NASA hosted on @drivendataorg
keerthigavnr/Intel-AI-oneAPI-Hackathon
A Domestic violence support system for the victims, that enables users to share their thought and provides knowledge about the particular type of abuse they are going through.
Arif-miad/Global-Plastic-Waste-Analysis
Global plastic waste is a pressing environmental issue, with massive production, limited recycling, and high risks to ecosystems and human health
aysecnkci/ObesityRisk-ML-Modeling
Machine learning project to predict obesity risk levels based on lifestyle and demographic data. This project utilizes advanced algorithms like CatBoost, LightGBM, and more to classify individuals into different obesity categories
bh-Abhishek-b/Web-Server-Log-Analysis
Web Server Log Analysis
DanniRodrJ/milling-machine_failure-prediction
Machine Learning aplicado al mantenimiento predictivo. Se realizaron 2 modelos: 1 por medio de clasificación binaria que predice si una máquina fresadora estará en riesgo de fallar o no, y el 2 modelo a través de clasificación multiclase que predecirá el modo de falla
dharmendradiwaker/Forecasting-House-Prices-Using-Machine-Learning
This project focuses on predicting house prices using machine learning techniques. The dataset consists of over 1,000,000+ rows and 12 columns containing information about various house attributes. The goal is to build predictive models to estimate house prices based on these attributes.
Egoluback/titanic_kaggle
A model classifying whether a person would survive on Titanic
emanueleiacca/Predict-LeagueTable-TurkishLeague
Final project for Sport Analytics class.
HendEmad/GraduationProject_Embedded-AI-Medical-Quadcopter
This repo includes Cardiac arrest prediction part, path planning, and landing system of the quadcopter.
Horeknad/Aeromole_auto_avia_offer_Aeroclub_hackathon
auto avia offer in Aeroclub hackathon
hperer02/Credit-risk-model
Discover a comprehensive approach to constructing credit risk models. We employ various machine learning algorithms like LightGBM and CatBoost, alongside ensemble techniques for robust predictions. Our pipeline emphasizes data integrity, feature relevance, and model stability, crucial elements in credit risk assessment.
issacchan26/CreditRiskPrediction
Data Analysis and prediction on Kaggle dataset: Credit Risk Dataset
kunalshelke90/Predict-Bank-Credit-Risk-using-South-German-Credit-Data
This is an end-to-end ML project, which aims at developing a classification model for the problem of classifying a given customer profile into either of the risk category (safe or not safe). The final classifier used for this project is CatBoost classifier. Deployed in AWS.
loopiiu/DSP2_Endterm
Expresso Churn Prediction Challenge - dealing with imbalanced dataset
ohincu/insurance-cross-selling
Identify health insurance customers with interest in a vehicle insurance.
Priya-cse/Zindi-New-User-Engagement
New User Engagement
seroetr/Disaster-Tweets-with-NLP
Disaster Tweets Classifications by Machine Learning, which is a currently Kaggle Competition.
AbhinavSinha02/OS-Threat-prediction-model-using-ML
This is a triage prediction model that classifies security threat based on the level of criticality.
ConradKleykamp/Loan-Approval-Prediction
Leveraging and tuning a LightGBM model to predict whether or not a loan will be approved
michael-bmstu/ecom-t_x_dls
Solution for competition of workshop ecom-t and Deep Learning School
ozerzeynep/DiabetesForecast
Diyabet Tespiti Projesi 💉
Abdelrahman-Amen/Heart_Diseases_with_deployment
This project focuses on predicting heart disease using a comprehensive dataset containing patient information. The goal is to build machine learning models that can predict the presence of heart disease based on various health parameters.
alaeddinee21/RH-analystics
This project predicts employee promotions using a CatBoost classifier. It preprocesses data by filling missing values, scaling numerical features, and encoding categorical data. The model pipeline includes SMOTE for handling class imbalance, aiming to accurately identify employees likely to be promoted.
alessioborgi/MLPipeline_OptimizationStudy
Exploration and optimization of a ML pipeline, delving into various techniques for enhancing different stages of ML workflows, including data preprocessing, feature engineering, model selection, and hyperparameter tuning.
AnnaAnastasy/Dibetes-Prediction-Logistic-KNN-Cat
Predicting diabetes using machine learning techniques. Starting with Logistic Regression as a baseline, it progresses to advanced models like Gradient Boosting.
Kunritty/Poisonous-Mushrooms-Classification
Data analysis and model training to predict whether mushrooms are poisonous or edible