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...
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...
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...
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...
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...
