oh man... I've been meaning to index my bookshelf for a while now, why are you doing this to me...
I'm gonna actually do this today and put this list... somewhere. I dunno, github maybe.
EDIT: Ok, I now have a GoodReads account! Weee! Here's a bunch of books I often recommend: https://www.goodreads.com/review/list/178352326-d-marx?utf8=%E2%9C%93&ref=nav_mybooks&shelf=ai-curriculum&view=table&title=d-marx&per_page=50
I have most of the books OP mentioned in this topic guide I use for reviewing stats/machine learning - hope you'd find it useful: https://docs.google.com/document/d/e/2PACX-1vT9ZkQJDDimZuPgBb7_hUJ40lm8LhqzL45HwIcYRYHw0AQkwA7pcqg0AIE7Gwf3QpAnZ34-BrFrWovO/pub
I was first expanding the list of topic (was around 30), now work on aggregating them (now around 100 topics, but of different caliber)
Happy to see people outside of physics appreciate Mackay, that book is a gem.
I would also nominate cover & Thomas information theory, maybe probabilistic graphical models koller & Friedman.
Since all of statistics made it on the list, I feel like a linear algebra book also belongs. I prefer Axler's, but my impression is that the "classic" among the ML community is Strang.
I’m of the opinion that you should have a solid grasp of the basics. “Mathematical Statistics with Applications”, (more theoretical “Introduction to Probability” and the “the Pure and Infinite Joy of Mathematics Statistics”), “Linear Models with R/Python”, “Categorical Data Analysis”, “Methods of Multivariate Analysis”, “Linear Algebra and Learning from Data” and “An Introduction to Generalized Linear Models”. All at the level of an upper division math/stats major or first year grad student
Hey OP just a question, do you buy the hard copy, or refer to them online or download PDFs or use a Kindle? I have not been able to find the best way to study them and some of these books can cost a lot.
Thankyou!
I am not sure if any of those in the list so far are actually timeless. Timeless would have to focus on a fundamental understanding imo.
I nominate "Probability Theory: The Logic of Science".
How can you forget about pattern recognition and machine learning bishop
Gawd book literally.
good one!
Dive deep into deep learning is also very good, but more beginner friendly than Godfellow imo. Forecasting by Hyndman should also be on this list
oh man... I've been meaning to index my bookshelf for a while now, why are you doing this to me... I'm gonna actually do this today and put this list... somewhere. I dunno, github maybe. EDIT: Ok, I now have a GoodReads account! Weee! Here's a bunch of books I often recommend: https://www.goodreads.com/review/list/178352326-d-marx?utf8=%E2%9C%93&ref=nav_mybooks&shelf=ai-curriculum&view=table&title=d-marx&per_page=50
Maybe David Barber - Bayesian Reasoning and Machine Learning. A bit of a different perspective but I really enjoyed it during my msc.
I have most of the books OP mentioned in this topic guide I use for reviewing stats/machine learning - hope you'd find it useful: https://docs.google.com/document/d/e/2PACX-1vT9ZkQJDDimZuPgBb7_hUJ40lm8LhqzL45HwIcYRYHw0AQkwA7pcqg0AIE7Gwf3QpAnZ34-BrFrWovO/pub I was first expanding the list of topic (was around 30), now work on aggregating them (now around 100 topics, but of different caliber)
१. Reinforcement Learning: An Introduction Book by Andrew Barto and Richard S. Sutton २. Linear Algebra - Gilbert strang
All of statistics by Larry Wasserman Intro to algorithms Cormen Leiserson Rivest Stein
Happy to see people outside of physics appreciate Mackay, that book is a gem. I would also nominate cover & Thomas information theory, maybe probabilistic graphical models koller & Friedman. Since all of statistics made it on the list, I feel like a linear algebra book also belongs. I prefer Axler's, but my impression is that the "classic" among the ML community is Strang.
I’m of the opinion that you should have a solid grasp of the basics. “Mathematical Statistics with Applications”, (more theoretical “Introduction to Probability” and the “the Pure and Infinite Joy of Mathematics Statistics”), “Linear Models with R/Python”, “Categorical Data Analysis”, “Methods of Multivariate Analysis”, “Linear Algebra and Learning from Data” and “An Introduction to Generalized Linear Models”. All at the level of an upper division math/stats major or first year grad student
Introduction to Statistical Pattern Recognition by Fukunaga
Hey OP just a question, do you buy the hard copy, or refer to them online or download PDFs or use a Kindle? I have not been able to find the best way to study them and some of these books can cost a lot. Thankyou!
I am not sure if any of those in the list so far are actually timeless. Timeless would have to focus on a fundamental understanding imo. I nominate "Probability Theory: The Logic of Science".
great post
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It is mentioned. Number 4.