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...
Numerical optimization

Numerical optimization

In our last discussion, we took a look at linear regressions using a marketing example centered around monthly sales. In addition to being able to fit our previous data sales, we’d also backed out a linear fit (with [math] r^2 = 0.965 [/math] that we could use...
Gaseous plume evolution

Gaseous plume evolution

Introduction    Our blog post on synthetic scene generation discussed the power of modeling realistic objects like terrain and vehicles,  applying material attribution, using the objects within a scene to simulate physics of a highly specific scenario. A second blog...