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Of interest to people who like the look of this book is Bishop's Pattern Recognition and Machine Learning, also available freely and legally online: https://www
by phonebucket 6y ago
Of interest to people who like the look of this book is Bishop's Pattern Recognition and Machine Learning, also available freely and legally online: https://www.microsoft.com/en-us/research/people/cmbishop/ https://www.microsoft.com/en-us/research/people/cmbishop/
- blackbear_ 6y agoAnd to close the triad of machine learning bibles, don't forget Murphy's, which will apparently be extended soon! https://probml.github.io/pml-book/ https://probml.github.io/pml-book/
- bonoboTP 6y agoI also like Alpaydin's Intro to ML even though it's not as famous: https://mitpress.mit.edu/books/introduction-machine-learning-fourth-edition https://mitpress.mit.edu/books/introduction-machine-learning...
- st1x7 6y agoSo much of that book just goes over my head while I didn't have that problem with ESL. I don't know if it's Murphy's writing style or just the way he approaches the topic but I found his book significantly more difficult to process.
- blackbear_ 6y agoOn the contrary, I like Murphy and cannot stand ESL. It probably boils down to what statistical camp you are more comfortable in.
- st1x7 6y agoMy problem is more with understanding, not necessarily with liking or disliking either book.
- dragandj 6y agoYes! They are just like the Bible. Concise, applicable, on the point, and you can learn so many useful (and true!) things from them.
- nextos 6y agoThere's also a newer book by Hastie (and Efron!), which I very much prefer to The Elements of Statistical Learning: Computer Age Statistical Inference. https://web.stanford.edu/~hastie/CASI_files/PDF/casi.pdf https://web.stanford.edu/~hastie/CASI_files/PDF/casi.pdf It's really well motivated and, unlike ESL, discusses many different schools---including classical inference, empirical and Bayes deep learning. Without these different perspectives, newcomers often find statistics very obscure as it just looks like a bag of tricks.
- pontus 6y agoI love this book so much. It takes a strong Bayesian point of view that makes things so clear to me. It's well written and we'll structured. It starts with a summary chapter of ML which honestly by itself gets you to a very good place in understanding the basics of ML.
- preommr 6y agoI remember putting this book in my pile almost a decade ago, is it still relevant?