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

Visualization dashboard of NYC green taxi data using plotly-dash

Final project of Course Applied Data Science @nyu CUSP

Data challenge of NYC taxi

Analysis of human behaviour in NYC using taxi data

Examine relationship between NYC weather and taxi data from 2016

Practice Programs of JAVABRAINS

Implementing Big Data Methods to Analyze 2017 NYC Yellow Taxi

End-to-End ETL pipeline for NYC Taxi data using Apache Airflow and PostgreSQL

NYC Green Taxi Data Analysis

NYC Green Taxi Tip Prediction

Built a few anomaly detection models to determine the anomalies from the data

Predicting the ride time of NYC taxi via machine learning theory

End-to-end pipeline to load, query, and analyze NYC Yellow Taxi trip data using MySQL and Python — includes Exploratory Data Analysis (EDA) and interactive dashboards built with Tableau.