The Taxi Fare Prediction project aims to develop a machine learning model that can accurately predict the fare
of a taxi ride based on various input features. These features include the pickup and drop-off locations, distance traveled,
duration, and number of passengers. By leveraging historical taxi ride data and incorporating these dynamic factors,
the project seeks to provide a robust solution for fare estimation.
The Movie Recommendation System project aims to deliver personalized movie recommendations to users by utilizing a combination of content-based filtering, collaborative filtering, and user-movie ratings prediction. By integrating these approaches, the system can provide accurate and relevant movie suggestions based on user preferences and historical data.
In this project we take raw housing data and transform
it in SQL Server to make it more usable for analysis.
This holds all of my Power BI Reports.
This holds all of my Tableau Dashboards.