How Google does Machine Learning

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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.

Aditya Jyoti Paul
Aditya Jyoti Paul
Technical Program Manager and CV/AI Researcher

My work makes machines smarter, secure and more accessible. I’m passionate about research, teaching and blogging. Outside academia, I love travel, music, reading and meeting new people!