4 ms·

This looks like it's using R to teach, primarily. I'm partial to "Collective Intelligence" (Toby Segaran's book)-- it's written with all python examples and app

by rd108 15y ago

This looks like it's using R to teach, primarily. I'm partial to "Collective Intelligence" (Toby Segaran's book)-- it's written with all python examples and appears to have much of the same content and approach (practical application > theoretical underpinnings).

eric_bullington 15y ago
I just received my copy of "Collective Intelligence" in the mail this morning, and immediately sat down and starting reading. I've been reading for the past several hours, non-stop. It's that good. Perhaps the best part is the chapter at the end of the book that neatly and concisely sums up all the major ML algorithms: neural networks, SVM, kNN, k-means, decision trees, Bayesian classifiers, etc. etc. This chapter alone is worth the price of the book. I only wish it were longer (and it's not a short book).
- levesque 15y ago
  What would you say is the level of the book? I am intrigued by your enthusiasm, but I think I'd be wasting my time if I went reading an introductory book.
  - rouli 15y ago
    I'd say it's introductory, up to the chapter it discusses SVMs. Than it becomes incomprehensible, unless you have prior knowledge of SVMs and kernel methods.
  - mrcapers 15y ago
    Introductory. I don't have a particularly formal background in discrete math or ML, but I was able to absorb most of the content.
- dbecker 15y ago
  You deserve a commission, Eric. I just bought "Collective Intelligence" based on your review.
  - haldean 15y ago
    Ditto. Here's an Amazon link, for the lazy: http://www.amazon.com/Programming-Collective-Intelligence-Building-Applications/dp/0596529325 http://www.amazon.com/Programming-Collective-Intelligence-Bu...
elemeno 15y ago
If you're using Python, what are you using for your stats libraries? R is, generally, the go to language for stats work I've found. It's certainly used a lot in the financial world for statistical modelling, and all the libraries in it are well tested which is a big plus in my book.
- carbocation 15y ago
  I'm also partial to R, but Python does have stats support via NumPy and (especially) SciPy: http://docs.scipy.org/doc/scipy/reference/stats.html http://docs.scipy.org/doc/scipy/reference/stats.html When I was at the Broad, at least, there was heavy use of both R and Python among the statistically savvy.
  - elemeno 15y ago
    Interesting - I'm not well versed on the Python stats ecosystem. It's a side effect of working in finance where every place I've worked already has large well tested libraries in C/C++/C#.
- gammarator 15y ago
  Here's a directory of stats/ML-related Python libraries: http://aliquote.org/memos/2011/02/07/python-for-statistical-computing http://aliquote.org/memos/2011/02/07/python-for-statistical-...
- pash 15y ago
  Scikits.statsmodels [1] is the main statistical and econometric library for Python. It is usually used with pandas [2], which provides nice interfaces to your data, particularly for time-series. You can also call R functions with the rpy2 bridge [3]; pandas provides a higher-level API for using rpy2, though last I checked it's not fully fleshed out yet. Wes McKinney, the developer of pandas, writes a blog [4] that provides a good look at data analysis in Python, particularly if you're in finance. 1. http://statsmodels.sourceforge.net/ http://statsmodels.sourceforge.net/ 2. http://pandas.sourceforge.net/ http://pandas.sourceforge.net/ 3. http://rpy.sourceforge.net/rpy2.html http://rpy.sourceforge.net/rpy2.html 4. http://blog.wesmckinney.com/ http://blog.wesmckinney.com/
fuzzythinker 15y ago
As mentioned in this thread http://news.ycombinator.com/item?id=3564873 http://news.ycombinator.com/item?id=3564873, there's another new book "Machine Learning in Action" from Manning uses python instead of R: http://www.manning.com/pharrington/ http://www.manning.com/pharrington/
gammarator 15y ago
I liked "Programming Collective Intelligence," as it fairly clearly introduces how the algorithms operate by implementing them from scratch. I found the coding style a bit non-pythonic, though (two space indentation?), and in practice you'd be better served using one of the many ML libraries (e.g., scikit-learn [1]), which aren't introduced. [1] http://scikit-learn.org/stable/index.html http://scikit-learn.org/stable/index.html
- weaksauce 15y ago
  The two space indentation is probably to fit more code on the page without softwraps.

by rd108 15y ago

eric_bullington 15y ago

I just received my copy of "Collective Intelligence" in the mail this morning, and immediately sat down and starting reading. I've been reading for the past several hours, non-stop. It's that good. Perhaps the best part is the chapter at the end of the book that neatly and concisely sums up all the major ML algorithms: neural networks, SVM, kNN, k-means, decision trees, Bayesian classifiers, etc. etc. This chapter alone is worth the price of the book. I only wish it were longer (and it's not a short book).

levesque 15y ago
What would you say is the level of the book? I am intrigued by your enthusiasm, but I think I'd be wasting my time if I went reading an introductory book.
- rouli 15y ago
  I'd say it's introductory, up to the chapter it discusses SVMs. Than it becomes incomprehensible, unless you have prior knowledge of SVMs and kernel methods.
- mrcapers 15y ago
  Introductory. I don't have a particularly formal background in discrete math or ML, but I was able to absorb most of the content.
dbecker 15y ago
You deserve a commission, Eric. I just bought "Collective Intelligence" based on your review.
- haldean 15y ago
  Ditto. Here's an Amazon link, for the lazy: http://www.amazon.com/Programming-Collective-Intelligence-Building-Applications/dp/0596529325 http://www.amazon.com/Programming-Collective-Intelligence-Bu...

elemeno 15y ago

If you're using Python, what are you using for your stats libraries? R is, generally, the go to language for stats work I've found. It's certainly used a lot in the financial world for statistical modelling, and all the libraries in it are well tested which is a big plus in my book.

carbocation 15y ago
I'm also partial to R, but Python does have stats support via NumPy and (especially) SciPy: http://docs.scipy.org/doc/scipy/reference/stats.html http://docs.scipy.org/doc/scipy/reference/stats.html When I was at the Broad, at least, there was heavy use of both R and Python among the statistically savvy.
- elemeno 15y ago
  Interesting - I'm not well versed on the Python stats ecosystem. It's a side effect of working in finance where every place I've worked already has large well tested libraries in C/C++/C#.
gammarator 15y ago
Here's a directory of stats/ML-related Python libraries: http://aliquote.org/memos/2011/02/07/python-for-statistical-computing http://aliquote.org/memos/2011/02/07/python-for-statistical-...
pash 15y ago
Scikits.statsmodels [1] is the main statistical and econometric library for Python. It is usually used with pandas [2], which provides nice interfaces to your data, particularly for time-series. You can also call R functions with the rpy2 bridge [3]; pandas provides a higher-level API for using rpy2, though last I checked it's not fully fleshed out yet. Wes McKinney, the developer of pandas, writes a blog [4] that provides a good look at data analysis in Python, particularly if you're in finance. 1. http://statsmodels.sourceforge.net/ http://statsmodels.sourceforge.net/ 2. http://pandas.sourceforge.net/ http://pandas.sourceforge.net/ 3. http://rpy.sourceforge.net/rpy2.html http://rpy.sourceforge.net/rpy2.html 4. http://blog.wesmckinney.com/ http://blog.wesmckinney.com/

fuzzythinker 15y ago

As mentioned in this thread http://news.ycombinator.com/item?id=3564873 http://news.ycombinator.com/item?id=3564873, there's another new book "Machine Learning in Action" from Manning uses python instead of R: http://www.manning.com/pharrington/ http://www.manning.com/pharrington/

gammarator 15y ago

I liked "Programming Collective Intelligence," as it fairly clearly introduces how the algorithms operate by implementing them from scratch. I found the coding style a bit non-pythonic, though (two space indentation?), and in practice you'd be better served using one of the many ML libraries (e.g., scikit-learn [1]), which aren't introduced. [1] http://scikit-learn.org/stable/index.html http://scikit-learn.org/stable/index.html

weaksauce 15y ago
The two space indentation is probably to fit more code on the page without softwraps.