Machine learning (ML)

As a wise uncle of a human-arachnid hybrid once said, With great power, comes great responsibility. This is very true of ML. There are many ways to go wrong. When in the hands of a skilled practitioner, it truly is a form of art. It can be used to do some incredible things on a grand scale, but it should come with a big caution sign. Use it carefully. Be paranoid and validate, validate, validate.

Although we will be going over some core concepts and providing code that you can take and run yourself, this is a big field with lots to learn. It takes years to skillfully and competently apply it. Each section in this chapter is really a book in itself. No, many books. If you plan to use it yourself on IoT data, read, read, read, and then read some more. This chapter is meant to able to provide you with a good foundation to have meaningful conversations with data scientists on the subject.

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