This project aims to analyse dataset on civil aviation accidents and particular occurrences that occurred within the United States, its territories, possessions, and the international waterways. I employ machine learning regression techniques to forecast the number of accidents and incidents, based on the available trend. The following three machine learning algorithms are used and contrasted, with different evaluation techniques in this Course Work; They are Generalized Linear Regression Model, Decision Tree Regression and Gradient-boosted Tree Regression. The Machine Learning (MLlib with pyspark) algorithms are made available in a Jupyter Notebook using the MLlib of Apache Spark and Big Data Analytics. Tableau desktop application is used to visualise the data.
Keywords: Airplane crash · Aviation safety · Accident cause analysis. Generalized Linear Regression Model. Decision Tree Regression . Gradient-boosted Tree Regression