The code presented in this chapter requires the following:
- Python 3.5+ (Anaconda distribution (https://www.anaconda.com/distribution/) is highly recommended)
- Libraries:
- SciPy 0.19+
- NumPy 1.10+
- scikit-learn 0.20+
- pandas 0.22+
- Matplotlib 2.0+
- seaborn 0.9+
The dataset can be obtained from the UCI machine learning repository. The CSV file can be downloaded from https://archive.ics.uci.edu/ml/datasets/water+treatment+plant and doesn't need any preprocessing, except for the addition of the column names, which will occur during the loading stage.
The examples are available on the GitHub repository: https://github.com/PacktPublishing/HandsOn-Unsupervised-Learning-with-Python/Chapter04.
