This repository is a case study of applying various machine learning models to the problem of predicting house prices.
The dataset is publicly available and can be downloaded, for example, at Kaggle.
The case study is based on this research paper.
A video presentation of the case study is available on YouTube 
.
The analyses are presented in four notebooks that may be interactively worked with by following these links:
- Notebook 0: Data Cleaning
- Notebook 1: Correlations
- Notebook 2: Visualizations
- Notebook 3: Predictions
The main goal is to show students how Python can be used to solve a typical data science task.
To be suitable for beginners, there are no formal prerequisites. It is only expected that the student has:
- a solid understanding of the English language and
- knowledge of basic mathematics from high school.
Some background knowledge in Python is still helpful.
To learn about Python and programming in detail,
this introductory course 
is recommended.
To follow this workshop, an installation of Python 3.8 or higher is expected.
A popular and beginner friendly way is to install the Anaconda Distribution that not only ships Python itself but also comes pre-packaged with a lot of third-party libraries including Python's scientific stack.
Detailed instructions can be found here .
As this project assumes a couple of third-party packages
that are not part of the Anaconda Distribution,
it is most likely necessary
to run the command pip install -r requirements.txt
before working with the notebook files.
Feedback is highly encouraged and will be incorporated.
Open an issue in the issues tracker
or initiate a pull request
if you are familiar with the concept.
Simple issues that anyone can help fix are, for example,
spelling mistakes or broken links.
If you feel that some topic is missing entirely, you may also mention that.
The materials here are considered a permanent work-in-progress.
Alexander Hess is a PhD student at the Chair of Logistics Management at WHU - Otto Beisheim School of Management where he conducts research on urban delivery platforms and teaches coding courses based on Python in the BSc and MBA programs.
Connect with him on LinkedIn.