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.

Analysis of human behaviour in NYC using taxi data

Code for fetching, sampling, and analysis of NYC taxi data from TLC and Uber for 2009-2018

Data challenge of NYC taxi

Examine relationship between NYC weather and taxi data from 2016

Machine learning project for NYC Yellow Taxi fare prediction. Complete data pipeline with DuckDB/Polars ETL, exploratory analysis of 34M trips, feature engineering, and ML model preparation. Achieves 0.954 correlation between distance and fare through comprehensive 2023 dataset analysis.

Visualization dashboard of NYC green taxi data using plotly-dash

Big Data analysis of NYC Yellow Taxi trips using Hadoop and Hive

Final project of Course Applied Data Science @nyu CUSP

Kubernetes-native data platform for NYC Taxi analytics — Lakehouse architecture with Iceberg, Spark, Airflow, Nessie(catalog), Rustfs(S3 compatible object storage), Trino, Superset.

Implementing Big Data Methods to Analyze 2017 NYC Yellow Taxi

NYC Green Taxi Data Analysis

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

Predicting the ride time of NYC taxi via machine learning theory