Sübeyte's repositories
Customer-Lifetime-Value-Prediction-Online-Retail-Dataset
CLTV is a method for predicting a how much a customer's going to create value for a firm in a specific time.
Recommendation_Systems-ARL-and-CF
Recommendation systems are among most widely preffered marketing strategies. Their popularity comes from close prediction scores obtained from relationships of users and items. In this project, two recommendation systems are used for two different datasets: Association Recommendation Learning and Collaborative Filtering. Please read the description for more info.
AB_Testing-Facebook_Bidding_Alternatives
AB Testing application for choosing right and effective bidding method on Facebook for a website.
End_to_End_Diabetes_Prediction
This project includes data preprocessing of the dataset, feature engineering and comparative prediction models with different machine learning methods.
RFM-KMeans-Comparison
RFM and K Means models are applied to Online Retail Dataset II.
Supermarket_App_BI-Analytics
LGBM and logistic regression for prediction of customers' second time transaction for an online market app.
Reliability-Analysis
Cronbach Alpha and Reliability Analysis functions.