Release Date: November 28, 2017
Today our guest is Kate Silverstein, a wicked smart machine learning engineer. (I say wicked because she's from Boston.)
Kate talks about the basics of Machine Learning (supervised vs. unsupervised learning, reinforcement learning), and then we review some product use cases (recommendation engines, SPAM filters, etc.) and describe how these features are powered by machine learning.
Kate even explains what the hell neural networks are.
Links mentioned in the episode
Racist AI (RE: loan application training data)
Google Sentiment API associating negative sentiment with certain minority groups
Courersa has a whole class on the Netflix Prize