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Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.
Learning Machines 101
Smart machines based upon the principles of artificial intelligence and machine learning are now prevalent in our everyday life. For example, artificially intelligent systems recognize our voices, sort our pictures, make purchasing suggestions, and can automatically fly planes and drive cars. In this podcast series, we examine such questions such as: How do these devices work? Where do they come from? And how can we make them even smarter and more human-like? These are the questions that will be addressed in this podcast series!
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Ratings & Reviews
4.5 stars from 129 ratings
A bit slow in pace
Suggest to be more straightful
no. Zhun via Apple Podcasts · Singapore · 04/10/20
Richard Golden provides an upbeat and positive introduction to Machine Learning. Whether you are a beginner in the field or an advanced practitioner, there is plenty to learn and enjoy in this podcast. Well done!
Greg Cathcart via Apple Podcasts · United States of America · 02/02/19
I’ll be back.
Very freaky, and it’s hard to follow along, it makes me feel very futile. And it was also very strange how I found out about this.they called didn’t answer me hung up and so I continued to call back and it said can’t not complete call at this time message LM 101. So I googled it “message LM101”...Read full review »
jay birbeck via Apple Podcasts · United States of America · 01/12/19
Recent Episodes
This 86th episode of Learning Machines 101 discusses the problem of assigning probabilities to a possibly infinite set of observed outcomes in a space-time continuum which corresponds to our physical world. The machine learning algorithm uses information about the frequency of environmental...
Published 07/20/21
Published 07/20/21
This 85th episode of Learning Machines 101 discusses formal convergence guarantees for a broad class of machine learning algorithms designed to minimize smooth non-convex objective functions using batch learning methods. Simple mathematical formulas are presented based upon research from the late...
Published 05/21/21
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