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
Computer Vision and Image Encryption 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!