Computational Introduction to machine learning

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The discussion centers on finding introductory resources for machine learning, specifically focusing on understanding the advantages and disadvantages of various machine learning methods without delving into implementation details. Participants highlight the importance of brushing up on statistics, with references to foundational texts such as "Introduction to Mathematical Statistics" by Hogg and Craig, "Data Reduction and Error Analysis" by Bevington, and "An Introduction to Error Analysis" by Taylor. A notable recommendation is the freely available "The Elements of Statistical Learning" by Hastie, Tibshirani, and Friedman, which is praised for its accessibility and comprehensive coverage of statistical learning concepts. There is also a suggestion to create a dedicated section for machine learning resources in the forum.
Frabjous
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Can anyone provide a good introductory reference to machine learning. Right now, I am interested in understanding the advantages and disadvantages of the various ML methods. I am not currently interested in detailed descriptions of their implementation.

I am probably going to have to brush up on my statistics. So I am also looking for a reference for this. Back in the day, I studied

Hogg,Craig Introduction to Mathematical Statistics (4th edition)
Bevington Data Reduction and Error Analysis
Taylor An Introduction to Error Analysis

although it is questionable how much I remember.
 
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