Abdelrahman Omran

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.

Learnings:

• Frame a business use case as a machine learning problem.
• Gain a broad perspective of machine learning and where it can be used.
• Convert a candidate use case to be driven by machine learning.

Skills: Application Programming Interfaces (API), Inclusive ML, Machine Learning, Google Cloud Platform, Bigquery