FROM DATA TO THESIS: Using Python for Non-Technical
Playground, Chapter 11: Introduction to Machine Learning in Python

How to use this project
1. Open this folder in VS Code, PyCharm, or your favourite Python editor.
2. Open exercises.py. It has four parts:
   A. Practise the chapter       the book's exercises with scikit-learn, blanks (______) to fill
   B. Go further                 new exercises beyond the book
   C. Check your understanding   short questions to answer in your own words
   D. Do it yourself             open tasks: no starter code and no answers
   Run each exercise cell or script in your editor.
3. Check parts A to C in solutions.py, after you have tried each one yourself.
   Part D has no solutions: the tasks are open, as in your own thesis.

The exercises need these packages (install once):
pip install pandas numpy scikit-learn matplotlib seaborn

Files
- exercises.py       the four parts, with starter code for parts A and B
- solutions.py       solutions for parts A and B, model answers for part C
- students.csv       one row per student in the wellbeing study (600 students)
- semesters.csv      one row per student per semester
- questionnaire.csv  the 22 questionnaire items
- titanic.csv        passenger survival on the Titanic (2,201 records)

Please note: Elaf and her data are fictional. The data was generated by a
computer program to look realistic, and its patterns were built in by the
author. It describes no real people and is not evidence about real students;
do not cite or use it as research findings.

The interactive browser playground version is at:
https://polla-fattah.github.io/data2thesis_python/playground/chapter11.html
