harshitaphadtare/GoPredict
End-to-end machine learning pipeline for trip duration prediction with feature engineering, regression models, and automated evaluation.
This project helps operations managers, dispatchers, or logistics planners accurately estimate travel times for deliveries, rides, or service calls. It takes in details like start and end locations, departure time, and city, then provides a predicted trip duration in minutes and a confidence score. This is designed for anyone needing reliable travel time predictions to optimize scheduling and resource allocation.
Use this if you need to predict trip durations for vehicles or people, considering factors like distance, time of day, and weather.
Not ideal if you need a simple route planner without machine learning-driven time predictions or if you only operate in a single, small geographic area.
Stars
13
Forks
18
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Nov 01, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/harshitaphadtare/GoPredict"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
michaelflppv/flight-delay-insurance
This is a repository of the educational project within "Deep Dive into Blockchain (DDiB)" Summer...
nive927/Flight_Delay_Prediction
A two-stage predictive machine learning engine that forecasts the on-time performance of flights...
junzis/atdelay
Air Traffic Delays Prediction Models
yankmo/DeepTP
基于深度学习的飞行轨迹预测系统，融合天气数据和飞行计划实现智能航迹预测
DanteSc03/Predicting-Flight-Delays
This project analyzes and visualizes airline delay causes using data sourced from Kaggle....