tushar2704/Seoul-bike-trip-duration
This repository contains the code and resources for predicting the duration of bike trips in Seoul, South Korea. Whether you're a data enthusiast, a bike-sharing enthusiast, or simply curious about predicting bike trip durations, this project has something for you.
No commits in the last 6 months.
Stars
1
Forks
—
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Aug 09, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/tushar2704/Seoul-bike-trip-duration"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
ChaitanyaC22/Udacity-AWS-MLE-ND-Project1-Bike-Sharing-Demand-with-AutoGluon
This project focuses on using the AWS open-source AutoML library, AutoGluon, to predict bike...
rameerez/bicimad-data-analysis
🚲 BiciMAD - Data analysis + ML usage predictions of Madrid's public bike system data
felipelodur/Bike-Sharing-Prediction-with-NeuralNet
Developed as coursework for Udacity "Deep Learning Fundamentals" Nanodegree
Aniket-Thopte/Demand-Forecasting-Public-Bike-Rental-Predictive-Modeling-
Developed multiple predictive models with 90% accuracy for forecasting the daily-hourly bike...
oyvinds78/trondheim-bus-ridership-prediction
Machine learning pipeline for predicting hourly bus ridership in Trondheim, Norway. Random...