Supervised ML: Fog prediction

Supervised ML: Fog prediction

Introduction In our tutorial on flight delay analysis, we scraped data from Kaggle. By ingesting a number of different data sources, we were able to piece together a large coherent dataset containing ~1.3M flights. Each flight in the dataset was further characterized...
Supervised ML: Flight delays

Supervised ML: Flight delays

Introduction Artificial Intelligence (AI) and Machine Learning (ML) have become a staple in today’s data analytics. Whether your problem lies in healthcare, fintech (finance technology), or transportation, ML provides a novel way to make predictions from large...
Signal processing: Flight delays

Signal processing: Flight delays

Introduction This article is an aside from a previous article on machine learning. The dataframe used in this tutorial (flown_noNA) is derived in the previous article after ingesting multiple CSV files, combining data, and removing redundancies within the resulting...
Multi-platform data collection

Multi-platform data collection

Introduction In the aerospace industry, there are two types of data: (1) synthetic data (e.g., models and simulations) or (2) experiments. Each has their own associated costs; while modeling and simulation require high-performance computers, graphical processing units...