A two-stage predictive machine learning engine that forecasts the on-time performance of flights for 15 different airports in the USA based on data collected in 2016 and 2017.

BJTU, trainning course, Predicting flight delays with weather data.

Our project focuses on predicting flight delays using machine learning techniques. We employ feature engineering and advanced regression algorithms to enhance accuracy. The dataset includes flight info, weather conditions, and other relevant factors. Our model achieves 94% accuracy.

Flight delays prediction and analysis: Machine Learning Approach

A machine learning at scale demo on flight delay prediction. The project includes an exploration of a series of data transformation and ML pipelines in Apache Spark (via Databricks).

Explore predictive modeling with this repository, featuring regression-based models applied to a comprehensive dataset on flight delays and cancellations. Gain insights into factors influencing air travel disruptions and leverage regression techniques to enhance predictions.

In this repo i developed predict a flight delay using machine learning.

Exploring supervised learning models on flight delay predictions.

A Two-Stage Predictive Machine Learning Engine to Forecast Flight On-Time Performance

Two stage model to predict if a flight is delayed and if so, the amount of delay in minutes. Trained using data from 18,00,000 flights of which ~ 30% were delayed

How can we better estimate flight delays?

Python project hosted in Google Colab that provides data visualizations & an interactive interface for flight delay prediction leveraging random forest

My Research Project on the prediction of Flight Delay due to Weather Conditions. Provided by Solarillion Foundation.

A two stage machine learning project to predict and calculate amount of flight delay.

This repository is a project that dealing with the problem of Flight scheduling

This project, Flight-Delay-Prediction, is a machine learning model that predicts flight delays using historical data from 2017, with a focus on logistic regression, decision trees, and random forests.

Flight Delay Prediction using ML

Analysis of Australian Domestic Flight delays using Markov Chains