Flight Delays Demo: ML/Classification, Generation of a Simple Model
Show how to generate a model from the raw flights data (flights data from 2018). Minimal cleanup or processing of the data is performed.
Details from the website:
The first step in any data analysis is to explore the raw data and try to get a feel for its organization and structure. This often involves creating summary (descriptive) statistics and visualizing the distribution and correlation of the variables in relation to one another. In this step of the project, we will use Python tools to dig into the flight delay data from the Department of Transportation.
Machine learning can help us analyze datasets with thousands or millions of features and tell us which are most important to an outcome of interest. In this step of the project we will create machine learning models and assess their predictive accuracy.