What is machine learning, and what kinds of problems can it solve? Google thinks about machine learning slightly differently – of being about logic, rather than just data.
We talk about why such a framing is useful for data scientists when thinking about building a pipeline of machine learning models. Then, we discuss the five phases of converting a candidate use case to be driven by machine learning, and consider why it is important the phases not be skipped.
We end with a recognition of the biases that machine learning can amplify and how to recognize this. >>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms of service <<<