Stephen Marsland 的《Machine Learning: An Algorithmic Perspective》非常好，如果你想在代码中看到这些想法，而且数学上还没准备好读 Hastie 或 Bishop 的话。http://seat.massey.ac.nz/personal/s.r.marsland/MLBook.html
"Machine Learning: An Algorithmic Perspective" by Stephen Marsland is very good if you want to see the ideas in code and if you're not mathematically ready for hastie or bishop. http://seat.massey.ac.nz/personal/s.r.marsland/MLBook.html
要领会其中许多技术的精髓，并用 Python 的 numpy/scipy 看实际例子，可以看看 Stephen Marsland 的《Machine Learning: An Algorithmic Perspective》。它没有其他书那样的数学深度或证明，但代码还不错，能让你开始做一些基本的数据分析。……
To get the spirit of many of these techniques with practical examples in python using numpy/scipy check out the book "Machine Learning: An Algorithmic Perspective" by Stephen Marsland. It doesn't have the mathematical depth or proofs found in these other books, but the code is decent and will get you started doing some basic data analysis.…
我想补充一下，Stephen Marsland 的《Machine Learning: An Algorithmic Perspective》是同一实用/入门类别中的一本新书。代码主要是 numpy。http://www-ist.massey.ac.nz/smarsland/MLbook.html
I'd like to add that Stephen Marsland's 'Machine Learning: An Algorithmic Perspective' is a new book in the same practical/introductory class. The code is mostly numpy. http://www-ist.massey.ac.nz/smarsland/MLbook.html
我手边有的：1. John R. Durbin 的《Modern Algebra》 2. Michael Sipser 的《Introduction to the Theory of Computation》 3. Stephen Marsland 的《Machine Learning - An Algorithmic Perspective》（水平不如上面两本，但仍然相当扎实） 我觉得 Tanenbaum 的操作系统和 Appel 的编译器书都属于这一类……
What I have in the room with me: 1. Modern Algebra by John R. Durbin 2. Introduction to the Theory of Computation by Michael Sipser 3. Machine Learning - An Algorithmic Perspective by Stephen Marsland (not quite on the same level as the above two, but still pretty solid) I think Tanenbaum's Operating System and Appel's Compilers books both go in this…
你可以看看 Stephen Marsland 的《Machine Learning: An Algorithmic Perspective》[0]，这本书讲机器学习时没那么依赖数学。代码在网上能拿到，想看得话可以去看看（是用 Python 写的）[1]。[0]: http://www.crcpress.com/product/isbn/9781420067187……
You can check out Machine Learning: An Algorithmic Perspective by Stephen Marsland[0] which takes a less math-driven approach to ML. The code is available online if you want to take a look at it (it's written in Python)[1]. [0]: http://www.crcpress.com/product/isbn/9781420067187…
…majors do for first 2 years, plus probability/stats: https://www.seas.harvard.edu/courses/cs281/#schedule http://www.zipfianacademy.com/blog/post/46864003608/a-practi... http://fastml.com/math-for-machine-learning/ ________ the general purpose programming languages mostly used are python, C++, java, and the statistical languages include R, matlab. there's lots of good threads at /r/machineLearning, including…
Stephen Marsland 的《Machine Learning: An Algorithmic Perspective》非常好，如果你想在代码中看到这些想法，而且数学上还没准备好读 Hastie 或 Bishop 的话。http://seat.massey.ac.nz/personal/s.r.marsland/MLBook.html
"Machine Learning: An Algorithmic Perspective" by Stephen Marsland is very good if you want to see the ideas in code and if you're not mathematically ready for hastie or bishop. http://seat.massey.ac.nz/personal/s.r.marsland/MLBook.html
要领会其中许多技术的精髓，并用 Python 的 numpy/scipy 看实际例子，可以看看 Stephen Marsland 的《Machine Learning: An Algorithmic Perspective》。它没有其他书那样的数学深度或证明，但代码还不错，能让你开始做一些基本的数据分析。……
To get the spirit of many of these techniques with practical examples in python using numpy/scipy check out the book "Machine Learning: An Algorithmic Perspective" by Stephen Marsland. It doesn't have the mathematical depth or proofs found in these other books, but the code is decent and will get you started doing some basic data analysis.…
我想补充一下，Stephen Marsland 的《Machine Learning: An Algorithmic Perspective》是同一实用/入门类别中的一本新书。代码主要是 numpy。http://www-ist.massey.ac.nz/smarsland/MLbook.html
I'd like to add that Stephen Marsland's 'Machine Learning: An Algorithmic Perspective' is a new book in the same practical/introductory class. The code is mostly numpy. http://www-ist.massey.ac.nz/smarsland/MLbook.html
我手边有的：1. John R. Durbin 的《Modern Algebra》 2. Michael Sipser 的《Introduction to the Theory of Computation》 3. Stephen Marsland 的《Machine Learning - An Algorithmic Perspective》（水平不如上面两本，但仍然相当扎实） 我觉得 Tanenbaum 的操作系统和 Appel 的编译器书都属于这一类……
What I have in the room with me: 1. Modern Algebra by John R. Durbin 2. Introduction to the Theory of Computation by Michael Sipser 3. Machine Learning - An Algorithmic Perspective by Stephen Marsland (not quite on the same level as the above two, but still pretty solid) I think Tanenbaum's Operating System and Appel's Compilers books both go in this…
你可以看看 Stephen Marsland 的《Machine Learning: An Algorithmic Perspective》[0]，这本书讲机器学习时没那么依赖数学。代码在网上能拿到，想看得话可以去看看（是用 Python 写的）[1]。[0]: http://www.crcpress.com/product/isbn/9781420067187……
You can check out Machine Learning: An Algorithmic Perspective by Stephen Marsland[0] which takes a less math-driven approach to ML. The code is available online if you want to take a look at it (it's written in Python)[1]. [0]: http://www.crcpress.com/product/isbn/9781420067187…
……专业头两年学的东西，再加上概率/统计：https://www.seas.harvard.edu/courses/cs281/#schedule http://www.zipfianacademy.com/blog/post/46864003608/a-practi... http://fastml.com/math-for-machine-learning/ ________ 通用编程语言主要用 python、C++、java，统计语言包括 R、matlab。/r/machineLearning 上有很多好帖子，包括……
…majors do for first 2 years, plus probability/stats: https://www.seas.harvard.edu/courses/cs281/#schedule http://www.zipfianacademy.com/blog/post/46864003608/a-practi... http://fastml.com/math-for-machine-learning/ ________ the general purpose programming languages mostly used are python, C++, java, and the statistical languages include R, matlab. there's lots of good threads at /r/machineLearning, including…