gradientboosting

ndtands/TabularDataProblem

Classification in TabularDataset

opennlp/Large-Scale-Text-Classification

Large Scale benchmarking of state of the art text vectorizers

rohitinu6/Lung_Cancer_Prediction_Using_Machine_Learning

Lung Cancer Prediction using Machine Learning Algorithms

cdalsania/Credit_Card_Fraud_Detection

This project researched the credit card transaction dataset and tried various machine learning classification models on the dataset to determine the best model that would flag suspicious activity more accurately.

ankanD1601/Amazon-Fine-Food

amir-rs/Prediction-of-osteoporosis-with-ML-and-NN

This project aims to detect bone fractures using machine learning and neural networks. It utilizes various machine learning models including AdaBoost, CatBoost, Logistic Regression, Random Forest, Support Vector Machine (SVM), XGBoost, Gradient Boosting, and LightGBM and and neural networks.

ankit013/Catboost

Implementing Catboost

bharanianand/Toyota-Corolla

Regression Analysis - Toyota Corolla price prediction

govardhan26/Heart-disease-blog

This is a blog of how machine learning algorithms are used to detect if a person is prone to heart disease or not.

hncpr1992/BlogFeedBackProject

saranggalada/ML_Superconductivity

Predicting the Critical Temperature of Superconductors using numerous Machine Learning techniques along with a comparative analysis of their performances.

tezzytezzy/caravan-insurance-policy

Random Forest Classification

alaaelkhashap/Apply-DT-Bagging-Boostingusing-Handwritten-Digits-Data-Set-

Classification Handwritten Digits

Ankita-Epari/Capstone-project-global-terrorism-

ankur727/NYC_Taxi_Trip_Time_Prediction

ML - Supervised - Regression

ArefMahjoubfar/fMRI-Classification-based-on-age-and-sex

a project for CNCS2021

aryamaansaha/employeeattrition

This repository contains code that was used to predict employee attrition using machine learning methods.

aviban12/Addicition-Prediction

EmanuelSommer/boosting_methods

[xgboost/ tidymodels/ bookdown] Boosting methods for regression: Theory and application in R

jazaoo13/WeatherPrediction

This project focuses on predicting the weather for the next day using a classification model. Both RandomForest and GradientBoosting classifiers were tested with grid search for hyperparameter tuning. The dataset used for this project is available at Kaggle.

luuisotorres/Detectando-Fraudes-de-Cartao-de-Credito-com-Machine-Learning

Utilizando algoritmos de classificação para criar um modelo preditivo que seja capaz de detectar fraudes de cartão de crédito.

Mgenthon/oc_p7

Ol0fmeistR/Recruit-Restaurant-Visitor-Forecasting

Used Machine Learning and time series forecasting to help Japanese restaurants predict their daily visitor frequency for the next 2 weeks using restaurant reservation data from HPGReserve and AirREGI.

Rajasri-kolli/Cesareandelivery-prediction

This study aimed to assess whether machine learning algorithms would outperform traditional modeling in developing a cesarean delivery prediction model among gravidas with morbid obesity (body mass index of ≥40 kg/m2) to determine whether a primary cesarean delivery may be beneficial.

ririraissa/Hotel_Cancelation_Order

When a customer places an order, the order may or may not be canceled later. To assist the hotel in minimizing losses it is necessary to analyze and predict the factors that lead customers to cancel their orders using machine learning model.

shihabmuhtasim/Machinearning-Model-Weather-Prediction-Rain-Snow-

This project aims to address the challenge of predicting whether it will rain or snow in Hungary based on various meteorological variables.

tianyiwangnova/2020_project__Starbucks_Ad_Campaign_Optimization

Based on the result data of an ad campaign experiment (randomly split the customers into control and experiemnt group), determine in the future what types of customers should be sent promotions to optimize the profit from ad

vrittigandhi/data_mining_project_22

Predicting popularity of movies using the IMDb movies dataset with multiple regression algorithms such as XGBoost, Gradient Boosting, Regularization Regressors, and Stacking Regressor; Performed extensive data cleaning, feature engineering, and used transformation techniques such as winsorization and log-transformation

alsgkals2/Ensemble_classification

Ensemble_classification

jbowles/JuML.jl

Machine Learning in Julia

jodiambra/Interconnect-Telecom-Churn-Predictions

The telecom operator Interconnect would like to forecast churn of their clients. To ensure loyalty, those who are predicted to leave will be offered promotional codes and special plans.

jwgwalton/credit_default_risk

Entries for the Kaggle Home Credit Group credit default competition.

sarathchandrikak/ML-by-Jovian

Course Work on Machine Learning covering Supervised and Unsupervised Algorithms

ShrishailSGajbhar/Coursera-Project

Final project for "How to win a data science competition" Coursera course

WangRongsheng/Classroom-PeopleCount

Classroom-PeopleCounting.