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

  • 2020/04/09
  • 再生時間： 37 分
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LM101-081: Ch3: How to Define Machine Learning (or at Least Try)

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  • 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 .
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あらすじ・解説

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 .
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