Organize some grid-based traffic flow datasets, mainly New York City bicycle and taxi data
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Updated
Jun 30, 2021
Organize some grid-based traffic flow datasets, mainly New York City bicycle and taxi data
Develop ML models predict taxi trip duration in NYC. Ranked : Top 6% | RMSLE : 0.377 (Kaggle) | #DS
In this project using New York dataset we will predict the fare price of next trip. The dataset can be downloaded from https://www.kaggle.com/kentonnlp/2014-new-york-city-taxi-trips The dataset contains 2 Crore records and 8 features along with GPS coordinates of pickup and dropoff
🗽🚕 Performance of data analysis in taxi trips in NYC and creation of a Random Forest Regressor in order to predict the duration of taxi trips.
Code for fetching, sampling, and analysis of NYC taxi data from TLC and Uber for 2009-2018
Final project of Course Applied Data Science @nyu CUSP
Examine relationship between NYC weather and taxi data from 2016
Visualization dashboard of NYC green taxi data using plotly-dash
Analysis of human behaviour in NYC using taxi data
Practice Programs of JAVABRAINS
Predicting the ride time of NYC taxi via machine learning theory
Built a few anomaly detection models to determine the anomalies from the data
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