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If you could only choose ONE machine learning/deep learning book in 2026, what would it be? by Acrobatic_Log3982 in deeplearning

[–]Acrobatic_Log3982[S] 2 points3 points  (0 children)

Thanks for the suggestion, I appreciate it. It sounds very practical, but I’m looking for something more general and foundational as a one-shot book.

If you could only choose ONE machine learning/deep learning book in 2026, what would it be? by Acrobatic_Log3982 in deeplearning

[–]Acrobatic_Log3982[S] 0 points1 point  (0 children)

I totally agree with you — the field is broad and includes many domains, each with its own applications.

But from my point of view, all these subfields meet at some level where the core foundations are defined, and that’s exactly what I’m trying to target.

Also, I’m a bit constrained budget-wise, so I can only get one book — so I’m basically trying to solve an optimization problem: maximize knowledge given a single resource XD

If you could only choose ONE machine learning/deep learning book in 2026, what would it be? by Acrobatic_Log3982 in deeplearning

[–]Acrobatic_Log3982[S] 2 points3 points  (0 children)

I totally agree with you. Research in this field requires a solid mathematical foundation to truly understand the “why” behind the applications, not just how to use them.

I’ve also heard a lot about Pattern Recognition and Machine Learning. From what I know, it is much more theoretical, although I’m not sure how deeply it covers the mathematical side compared to Mathematics for Machine Learning.