This project, done for GA Tech, explores relationship between health factors and hospitalization in NHANES dataset
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Updated
Apr 19, 2019 - R
This project, done for GA Tech, explores relationship between health factors and hospitalization in NHANES dataset
Ist Place Solution
Predicting CDGO e-sport match winners using XGBoost Trees
İstanbul Ev Fiyatları Tahmin Modellemesi
Predicting binary outcomes (kill or error) in volleyball to produce an Expected Kills (xK) model.
Imbalanced classification with loan clients dataset.
Sample data of Indian Domestic flights operated between march and june of 2019 was explored. Machine learning models that predicts the cost of the ticket was built.
Project to produce supervised ML algorithm to predict which customers are likely to leave and produce .Rmd report
This project studies and visualizes the original data and creating new attributes in the dataset which will cater to the exploratory data analysis. This is a small attempt into viewing this problem as a classification problem using a simple XGBoost model that provides a basic prediction (still working on the final part).
It is important that credit card companies are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase. Here, the aim is to analyze the dataset and detect the fradulent transactions.
Scrape YA students apartment data and build a rental cost prediction model
Code for the Kaggle competition "Mercedes-Benz Greener Manufacturing"
FIFA'19 datasets Analysis
Studies consumer preferences and industry priorities in the restaurant industry using supervised and unsupervised machine learning.
The objective of the project is to create a machine learning model. We are doing a supervised learning and our aim is to do predictive analysis to predict housing price.
A hybrid classification and prediction model for credit risk analysis in R
A predictive analytics model for a Kaggle competition to predict the price of car using a dataset containing information on 40,000 used cars.
Artificial Intelligence-based Prediction of Acute Leukemia: a free and open-source software package built in R, with a user-friendly interface provided via Shiny, that enables clinical hematologists and biologists to diagnose the three main subtypes of acute leukemia based solely on 10 routine biological parameters.
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