Machine Learning Project on Resume Screening using Python

This project aims to predict online shoppers' purchase intentions using browsing history and user data from e-commerce sites. By analyzing clickstream and session information, the goal is to create a machine learning model that accurately forecasts customers' likelihood of making a purchase.

This project is to build a model that *predicts the human activities* such as __Walking, Walking_Upstairs, Walking_Downstairs, Sitting, Standing__ and __Laying__ as done in Smart-Watches.

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This repository contains data analysis programs in the Python programming language.

This project showcases skills in machine learning, data preprocessing, and model evaluation using Python libraries such as scikit-learn, XGBoost, and Optuna. It involves implementing various machine learning models, handling imbalanced data, and employing imputation techniques to enhance model performance for predicting cirrhosis outcomes.

Data Gathering -> Data Cleansing -> Data Preprocessing -> Data Visualization