This project contains a notebook along with a complete Data Science project and analysis to illustrate some of the following concepts from the Udacity Data Science Nanodegree program.
- CRISP-DM compliance
- Dealing with missing data
- Steps to fitting, making predictions and evaluating a supervised machine learning model
- Answering targeted questions pertaining to the dataset to form a succinct data story with visualizations
- Sharing a compelling story by way of a Medium post
There is one python notebook within this repository that showcases the end-to-end analysis as summarized for business users in a Medium post available here.
Complete results of this analysis are shared within the project notebook as well as the medium post linked here.
Must give credit to Stack Overflow for the data. You can find the Licensing for the data and other descriptive information at the link available here.
Several references, especially towards the intialization, fit and evaluation of a model refer to best practices as documented in Udacity's Data Science Nanodegree program.