Machine Learning
by Tom M. Mitchell · first published 1997
59% recommend37% neutral4% critical
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Hi, machine learning PhD here - one way you can start is by brushing up on some fundamentals. A book such as Machine Learning, by Thom M. Mitchell is a reasonable start. Also, in terms of applying ML, you could scoot through…
on “Ask HN: I'm getting a new job that involves machine learning. How do I kick ass?” ↗Machine Learning by Tom Mitchell for a serious academic book. Programming Collective Intelligence by Toby Segaran for a practical approach in Python.
on “Can anyone recommend good books, articles or essays that introduce machine learning?” ↗My favorite introductory textbook on machine learning is the Tom Mitchell book: http://www.amazon.com/Machine-Learning-Tom-M-Mitchell/dp/007... The Bishop book is the most popular though: http://www.amazon.com/gp/product/0387310738/ref=pd_rvi_gw_2/...
on “Research Blog: Machine Learning Book for Students and Researchers” ↗…is very approachable and presents some very interesting topics (so you won't write a regex for matching HTML and will learn what P vs NP means). On a more practical side, I think that a must read for machine learning is Tom Mitchell - Machine Learning . Another book that from what I've heard is easier to digest is Data Mining: Practical Machine Learning Tools and Techniques.
on “Must Read CS Books For Self Self-Taught Programmers” ↗This is kind of a masters degree course i created for myself to get knowledge of Machine Learning from bottoms up First, you need a strong mathematical base. Otherwise, you can copy paste an algorithm or use an API but you will not get any idea of what is happening inside Following concepts are very…
on “Ask HN: How to Seriously Start with Machine Learning and AI” ↗I think many (if not most) topics don't have such an obvious single authorative source. Machine Learning: Tom M. Mitchell
on “Ask HN: What is the equivalent K&R book for (insert any topic here)?” ↗Sidenote: I highly recommend Tom Mitchell's (the professor) book as a general introduction to the topic. [0]: http://www.amazon.com/Machine-Learning-Tom-M-Mitchell/dp/007...
on “CMU professor at forefront of machine learning research” ↗For a really nice introductory book, try "Machine Learning" by Tom Mitchell.
on “Level-Up Your Machine Learning” ↗…above keywords refer, may or may not have been covered by the article. The keywords themselves are however absent. Additional reading suggestions: - Jon Bentley's Programming Pearls - Tom Mitchell's Machine Learning - Douglas Hofstadter's Gödel, Escher, Bach - Brian Kernighan and Rob Pike's Unix Programming Environment
on “What Every Computer Science Major Should Know” ↗…Post Script - Some book recommendations for beginners. 1. Linear Algebra by Gilbert Strang 2. Calculus by Gilbert Strang 3. Artificial Intelligence A Modern Approach By Russell and Norvig 4. Machine Learning By Tom Mitchell 5. Neural Networks for Pattern Recognition by Chris Bishop 6. Paradigms of Artificial Intelligence Programming by Peter Norvig (ok, this one is not quite an cutting edge AI book,…
on “Self-learning is overrated (in programming)” ↗Tom Mitchell's Machine Learning book (http://www.cs.cmu.edu/~tom/mlbook.html) is the one book from college that I go back to again and again.
on “Semisupervised Learning Approaches (Tom Mitchell)” ↗Tom Mitchell's Machine Learning is also very good (despite being a bit older) http://www.cs.cmu.edu/~tom/mlbook.html
on “How I Would Use the Google Prediction API (To Find Your Musical Profile)” ↗Sure. 1. Introduction to the Theory of Computation - Sipser and Introduction to Algorithms - CLRS (for the Algorithms course) 2. Machine Learning - Tom Mitchell 3. Artificial Intelligence - A Modern Approach - Russell and Norvig 4. Design of Everyday Things - Norman (for HCI) 5. Operating Systems in Three Easy Pieces [0] Most of the courses…
on “Ask HN: Master of Science in Computer Science at Georgia Tech” ↗Tom Mitchell book is still a great book to understand what Machine Learning is about
on “On moving from statistics to machine learning, the final stage of grief (2019)” ↗This may not be a sexy idea but one example I can thing of Tom Mitchell’s Machine Learning book, it gives the bare bones of what machine learning is (albeit it is missing some of the newer architectures) but that gives a great overview of how to build these architectures from scratch
on “Ask HN: Tutorials written with heavy dependencies” ↗