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ML is a super overloaded term.

There are definitely cases where machine learned statistical solutions do not perform as well as the systems tuned by the experts, but if you can define the task well and get the data for a deep solution, usually those will overtake.




This. I believe technically just linear regression could be considered "machine learning".


I've seen people at bio conferences actively calling linear regression machine learning.


This is likely because linear regression meets most widely accepted definitions of machine learning. [0][1] It is simple and very effective when learning in linear space.

[0] https://en.wikipedia.org/wiki/Machine_learning

[1] https://www.cs.cmu.edu/~tom/mlbook.html


Sorry, I don’t get it. Are you saying fitting a linear regression model to data and making predictions somehow isn’t machine learning? I am confused.




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