This is meant to be a showcase of stuff I'm playing around with, struggling with or obsessing about.
Its arranged as follows :
- Entire projects are in the Projects folder. My attempt here is to try to answer as many questions as I can. Ideally it would try spanning the entire data science pipeline, from data to data product. These folders include
- Data stories ( in the README.mds)
- Data analyses
- Machine Learning Prediction algorithms
- Dashboards
- the data used for all these analyses (unless its sensitive data)
- One-off analyses usually demonstrating a quick demo of a library, technique or concept.
- If the goal of the notebook is to explain a technique, then the choice of data is deliberately simple (for e.g. iris, cars). I feel this prevents focus on the data and enables the reader to focus on the technique.
- Some are complete, some ...meh!
Important notes in red.
TODOs in green. Ill revisit whenever I can.
Please remember that most of the projects are work in progress(w.i.p) unless specified so..because a data science project never ends (err....also I work on these during off hours and when Im not day dreaming.)