LM101-081: Ch3: How to Define Machine Learning (or at Least Try)

Learning Machines 101

Richard M. Golden, M.S.E.E., and B.S.E.E. द्वारा प्रदान की गई सामग्री. एपिसोड, ग्राफिक्स और पॉडकास्ट विवरण सहित सभी पॉडकास्ट सामग्री Richard M. Golden, M.S.E.E., and B.S.E.E. या उनके पॉडकास्ट प्लेटफ़ॉर्म पार्टनर द्वारा सीधे अपलोड और प्रदान की जाती है। यदि आपको लगता है कि कोई आपकी अनुमति के बिना आपके कॉपीराइट किए गए कार्य का उपयोग कर रहा है, तो आप यहां बताई गई प्रक्रिया का पालन कर सकते हैं https://hi.player.fm/legal।

5+ y ago 37:20

MP3•एपिसोड होम

This particular podcast covers the material in Chapter 3 of my new book "Statistical Machine Learning: A unified framework" with expected publication date May 2020. In this episode we discuss Chapter 3 of my new book which discusses how to formally define machine learning algorithms. Briefly, a learning machine is viewed as a dynamical system that is minimizing an objective function. In addition, the knowledge structure of the learning machine is interpreted as a preference relation graph which is implicitly specified by the objective function. In addition, this week we include in our book review section a new book titled "The Practioner's Guide to Graph Data" by Denise Gosnell and Matthias Broecheler. To find out more information visit the website: www.learningmachines101.com .

85 एपिसोडस

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