
Data Science Case Study: EDA on Mystery Science
EDA using Data Science tools: Python, Data Visualizations, Machine Learning, Statistical Tests and Inference, a Custom Build ML Tool, and more!
Sep 6, 2018 · 1 min read
What’s Mystery Science?
The above gist is an exhaustive data analysis on Mystery Science (MS) data. MS is a San Francisco based startup that is working towards improving the K-5 science curriculum in the United States and across the world.
What’s in the Notebook?
The notebook demonstrates a typical EDA workflow on industry data. Tools like data visualization, machine learning, and statistics are all combined to provide a thorough analysis and answer some business critical questions.
Why should the reader care?
If you’re someone that interested in learning how to:
- Comprehensively use the data science tool box
- Learn about the data and model error through iterative modeling building
- Feature Engineer the right features
- Write efficient code for EDA workflows
Then you can benefit from reading this notebook!
