Predicting Flight Delays in Azure ML Studio

Building a Regression Model in Azure

A Python utility for command-line interaction with Azure Machine Learning model endpoints. I built this as a testing interface for a flight delay prediction model trained with Azure's AutoML.

Tech Stack

  • Python
  • Azure ML Studio (AutoML)
  • Requests library

How It Works

AutoML handled feature engineering, algorithm selection, and hyperparameter tuning. I wrote a CLI tool to send prediction requests to the deployed endpoint with flight parameters (origin, destination, departure, arrival times) as arguments.

Results

  • R² Score: 0.80
  • Normalized RMSE: Under 0.1

Solid first-pass results. The model captured most of the variance in the data and made consistent predictions across the range of values.

What I Learned

Compared to building a model from scratch, AutoML trades granular control for speed. It tested multiple algorithms and configurations in parallel and handled the infrastructure, so no GPU driver headaches like I had on Lambda Labs.

The inference script is on my GitHub.