NY Taxi Trip

This project analyzed NYC Yellow Taxi trip data to uncover insights and build predictive models. #The dataset was cleaned by handling missing values and ensuring date-time consistency. #Exploratory Data Analysis (EDA) identified high-demand areas, peak ride times, fare distribution, and the impact of external factors like weather. # Various machine learning models, including tree-based and supervised/unsupervised learning approaches, were applied to predict ride duration and fare prices based on trip distance, time of day, and passenger count. # Data visualization techniques were used to present key findings effectively