4 ms·

You're not asking about anything about computer vision, if you're asking just about Caffe and Tensorflow. You're not even asking about the whole of machine lear

You're not asking about anything about computer vision, if you're asking just about Caffe and Tensorflow. You're not even asking about the whole of machine learning: you're just asking about neural networks. If you haven't done significant mathematical stuff by yourself (like, do all the problems in a math book by yourself without anyone else telling you what to do), go get a degree. MS in CS is probably best, those are surprisingly easy to get into. Otherwise, Haykin's Neural Networks and Learning Machines is best in my opinion (http://www.amazon.com/Neural-Networks-Learning-Machines-3rd/dp/0131471392 http://www.amazon.com/Neural-Networks-Learning-Machines-3rd/...). Bengio's Deep Learning book is the most current by far (http://www.deeplearningbook.org/ http://www.deeplearningbook.org/). Otherwise, you read papers. Note that all of these will deal nearly exclusively with the mathematics. Otherwise, you are following tutorials and wouldn't need any actual knowledge to do things. Some of the mathematics is a year old: some of the mathematics is 50 years old, some of it has been around since Gauss.

e19293001 10y ago
With a knowledge in college algebra, what math book would you study next?
- curuinor 10y ago
  If by "college algebra" you mean, abstract or modern algebra (groups, rings, fields, modules, vector space, lattices, etc), I would throw away the modern algebra book (for now: there are some applications of topology and topology-related parts of algebra, but without a solid grounding in analysis and numerical computing you won't get anywhere) and get some analysis books. (baby (Principles of Mathematical Analysis) along with big (Real and Complex Analysis) Rudin if you want to do theoretical things, or just normal calculus books like Spivak's if you want to do things). Then, learn computational linear algebra (I'm not appraised of too many great books in this, although try looking at the ee263 notes for Stanford, for linear dynamical systems (http://web.stanford.edu/class/archive/ee/ee263/ee263.1082/notes/ee263coursereader.pdf) http://web.stanford.edu/class/archive/ee/ee263/ee263.1082/no...) If by "college algebra" you mean that you learned basic algebra (fundamental theorem, equation solving, memorize solution to quadratic equation) in college, you need to learn calculus in one and then many dimensions (most of the people I know who are doing research-level things in machine learning learned this stuff in 6th to 8th grade, but who cares, especially if you are merely doing applications). Then, you learn linear algebra.

e19293001 10y ago

With a knowledge in college algebra, what math book would you study next?

curuinor 10y ago
If by "college algebra" you mean, abstract or modern algebra (groups, rings, fields, modules, vector space, lattices, etc), I would throw away the modern algebra book (for now: there are some applications of topology and topology-related parts of algebra, but without a solid grounding in analysis and numerical computing you won't get anywhere) and get some analysis books. (baby (Principles of Mathematical Analysis) along with big (Real and Complex Analysis) Rudin if you want to do theoretical things, or just normal calculus books like Spivak's if you want to do things). Then, learn computational linear algebra (I'm not appraised of too many great books in this, although try looking at the ee263 notes for Stanford, for linear dynamical systems (http://web.stanford.edu/class/archive/ee/ee263/ee263.1082/notes/ee263coursereader.pdf) http://web.stanford.edu/class/archive/ee/ee263/ee263.1082/no...) If by "college algebra" you mean that you learned basic algebra (fundamental theorem, equation solving, memorize solution to quadratic equation) in college, you need to learn calculus in one and then many dimensions (most of the people I know who are doing research-level things in machine learning learned this stuff in 6th to 8th grade, but who cares, especially if you are merely doing applications). Then, you learn linear algebra.