A deep learning approach for combining time-series and textual data for taxi demand prediction in event areas
The primary objective of this project is to build a Real-Time Taxi Demand Prediction Model for every district and zone of NYC.
Taxi Demand prediction using text processing for different zones in brooklyn, New York.
Taxi Demand Prediction is a Flask web app that forecasts short-term taxi demand across New York City using zone-based clustering and historical trip data. It provides an interactive dashboard for selecting a zone and time, viewing demand predictions, trends, and nearby higher-demand areas.
This GitHub repository contains code and resources for a real-world case study of New York taxi demand prediction using machine learning.
The primary objective of this project is to build a Real-Time Taxi Demand Prediction Model for every district and zone of NYC.
New York Yellow Taxi Demand prediction regression DSLS2023 Selection
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