Python practice

Let's do first an example of anomaly detection, then another for CPD. Let's first look at the needed libraries in the next section.

Requirements

In this chapter, we'll use several libraries, which we can quickly install from the terminal (or similarly from the anaconda navigator):

pip install ruptures alibi_detect

We'll execute the commands from the Python (or IPython) terminal, but equally we could execute them from a Jupyter notebook (or a different environment).

We should be ready now to get into the woods with implementing unsupervised time-series algorithms in Python.

Anomaly detection

alibi-detect comes with several benchmark datasets for time-series anomaly detection:

• fetch_ecg—ECG dataset from the BIDMC Congestive Heart Failure Database
• fetch_nab—Numenta Anomaly Benchmark
• fetch_kdd—KDD Cup '99 dataset of computer network intrusions

The last of these is...