A deep learning approach for combining time-series and textual data for taxi demand prediction in event areas
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Updated
Aug 17, 2018 - Jupyter Notebook
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.
This GitHub repository contains code and resources for a real-world case study of New York taxi demand prediction using machine learning.
New York Yellow Taxi Demand prediction regression DSLS2023 Selection
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