A Concise Explanation of Learning Algorithms with the Mitchell Paradigm

A Concise Explanation of Learning Algorithms with the Mitchell Paradigm

Source: Matthew Mayo, KDnuggets

A single quote from Tom Mitchell can shed light on both the abstract concept and concrete implementations of machine learning algorithms.

A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.

– Tom Mitchell, “Machine Learning”

Tom Mitchell’s quote is well-known and time-tested in the world of machine learning, having first appeared in his 1997 book. The sentence has been influential on me, personally, as I have referred to it numerous times over the years and referenced it in my Master’s thesis. The quote also features prominently in Chapter 5 of the much more recent and authoritative “Deep Learning” by Goodfellow, Bengio & Courville, serving as the jumping off point for the book’s explanation of learning algorithms. Read entire article…

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