37 results for “topic:nyc-taxi”
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
No description provided.
🗽🚕 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
Analysis of human behaviour in NYC using taxi data
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.
Data challenge of NYC taxi
No description provided.
Visualization dashboard of NYC green taxi data using plotly-dash
Final project of Course Applied Data Science @NYU CUSP
Big Data analysis of NYC Yellow Taxi trips using Hadoop and Hive
NYC Green Taxi Data Analysis
Implementing Big Data Methods to Analyze 2017 NYC Yellow Taxi
Snowflake + dbt mini-warehouse on NYC Yellow Taxi (Parquet → RAW → ANALYTICS → dbt docs)
NYC Green Taxi Tip Prediction
No description provided.
A machine learning pipeline to predict taxi tip probability using the NYC TLC 2025 Yellow Taxi dataset, including EDA, an sklearn Pipeline, and classification models.
End-to-End ETL pipeline for NYC Taxi data using Apache Airflow and PostgreSQL
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.
Built a few anomaly detection models to determine the anomalies from the data
NYC Taxi demand forecasting using machine learning and weather analytics. Includes end-to-end pipeline: data preprocessing, feature engineering, XGBoost forecasting, and Power BI dashboards.
A data-driven analysis of NYC Green Taxi trips focusing on demand patterns over time and location, fare-related factors, and passenger behavior. The insights aim to support service improvements and strategic decision-making.
Neural network model for predicting NYC taxi fares - CAP4770 Final Project
Business Intelligence & Analytics — Geospatial ride-hailing analysis + Bitcoin social-media sentiment research (CMU, Prof. Beibei Li, 2021)
End-to-end CRISP-DM forecasting pipeline for hourly NYC taxi demand using classical ML, tree ensembles, Conv1D+LSTM deep learning, and hybrid blending.
Reactive Marimo notebooks exploring NYC taxi data and the impact of congestion pricing (Jan 2025). DuckDB, Polars, Plotly.