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  1. Salary-Prediction-Project-of-US-Baseball-Major-League-Players-with-Thirteen-Different-Machine-Learni Salary-Prediction-Project-of-US-Baseball-Major-League-Players-with-Thirteen-Different-Machine-Learni Public

    In this project, thirteen different machine learning models were employed to predict salary of any US Major Baseball League player. These are Linear Regression, Ridge Regression, Lasso Regression, …

    Jupyter Notebook 2

  2. AB-Test-for-the-Comparison-of-Bidding-Types AB-Test-for-the-Comparison-of-Bidding-Types Public

    For this study, I wanted to use Independent Two Samples T Test as an A/B Test to compare the groups; however, though homogeneity of variance was met, normality assumption was not met for Average Bi…

    Jupyter Notebook 1

  3. Customer-Churn-Prediction-by-Using-Apache-Spark-PySpark- Customer-Churn-Prediction-by-Using-Apache-Spark-PySpark- Public

    The purpose of this study is to build a customer churn prediction model by using the data of a bank's custumers. This project is a sample of a big data project by using PySpark. Since it was not po…

    Jupyter Notebook 1

  4. Customer-Segmentation-by-Using-KMeans Customer-Segmentation-by-Using-KMeans Public

    In this project the customers of a company were segmented based on recencey, frequency, and monetary (RFM) metrics. After finding RFM metrics, KMeans Machine Learning Method was used to group the c…

    Jupyter Notebook

  5. Time-series-analysis-of-the-daily-page-views-for-the-Wikipedia Time-series-analysis-of-the-daily-page-views-for-the-Wikipedia Public

    Time series analysis by using Facebook Prophet. This project is a replication of the project on facebook. In this project I predicted the daily page views for the Wikipedia page for Peyton Manning …

    Jupyter Notebook

  6. Predicting-Boston-House-Prices-by-Using-Azure-Databricks Predicting-Boston-House-Prices-by-Using-Azure-Databricks Public

    In this study Boston House Prices were predicted by using Azure Databricks platform. The data includes the home values of Boston in 1970's. Five of the 14 diverse variables were used for this small…

    Python