In this repository, I am using SpaceX Falcon 9 launch data to predict landing success of a launch. This project is based on the Applied Data Science Capstone course, which is the last course of Coursera's Data Science Professional Certificate.
However, I have improved not only many of the analyses in order to improve that prediction, but I have also increased the detail in the explanations of what is being done in each line of code. This repository is composed of an introduction/methodology file, several exploratory data analyses files and a results/discussion file coming from the modeling approaches used.
I strongly recommend the use of NB Viewer to visualize the files so that the images and the maps included can become visible.
Introduction to the problem and general methodology used.
Exploratory data analysis and data preparation for model development.
Data standardization, split into training and test data, model fit using logistic regression, decision tree, support vector machine and
Analysis of launch site location in terms of its distance to the nearest lines of communication, the coastline and to the nearest city.
An alternative way to obtain data on SpaceX launches. Instead of using the API from the SpaceX website, in this file the data was scraped from a Wikipedia web page.