Let's now put what we have learned into practice. We are going to build a diagnostic analytic and a predictive analytic. We will develop an anomaly detection algorithm for an airplane and a predictive algorithm for an oil and gas refinery. We want to remain as generic as possible, so we won't make any assumptions about the system that we are going to monitor.
We will develop these two use cases with Python, SciPy, NumPy, Seaborn, and Pandas. We will assume that Anaconda 5.2 or Python 3.7 are already installed on your system.
For your convenience Jupyter Notebook are available at the official Github repository https://github.com/PacktPublishing/Hands-On-Industrial-Internet-of-Things . To work with Jupyter Notebook, open command console on the Chapter13 directory, then you can run from command console:
jupyter notebook
