5 ms·

Introduction to Data Mining – Second Edition

236 points by wener 8y ago

Phithagoras 8y ago
text available at http://gen.lib.rus.ec/search.php?req=introduction+to+Data+mining+ning&open=0&res=25&view=simple&phrase=0&column=def http://gen.lib.rus.ec/search.php?req=introduction+to+Data+mi...
- toonervoustosay 8y ago
  you're linking to an illegal ebook sharing web site this is against policy
- godelmachine 8y ago
  Thanks for the link :)
- shawn 8y ago
  Thank you.
- zekrioca 8y ago
  that's the 1st edition, not the 2nd as linked in the title
  - shawn 8y ago
    True, but if you make the query a bit more general and sort by year, you get some wildly interesting results: http://gen.lib.rus.ec/search.php?&req=%E2%88%86introduction+to+Data+mining&phrase=0&view=simple&column=def&sort=year&sortmode=DESC http://gen.lib.rus.ec/search.php?&req=%E2%88%86introduction+...
- lizhang 8y ago
  Thanks!
shawn 8y ago
Great! I was just reading through the first edition this week. It's excellent. Also see Mining of Massive Datasets: http://infolab.stanford.edu/~ullman/mmds/book.pdf http://infolab.stanford.edu/~ullman/mmds/book.pdf
mark_l_watson 8y ago
Looks great. I just looked through the 3 free chapters and saved them for later reading.
blackmario 8y ago
Thanks!
Puer 8y ago
I'm excited to take this class this fall at the U of M. I've heard that the fall course is more algorithmically rigorous than the spring course because the computer science department tries to open it up to non-CS majors at that time (biology majors interested in bioinformatics, for example). The professor, George Karypis, has a reputation on campus. I'm doing a dual degree in statistical science and CS so I'm looking forward to seeing how this compares to some similar class offered by the stats department.
technofiend 8y ago
At textbook pricing this is not a casual purchase. Hopefully this is not a trend; I'd hate to see the next O'Reilly book priced north of $60.
- johnsonjo 8y ago
  Well I’m pretty sure it is a textbook (by Pearson a textbook publisher) put together by research PHDs in Data Mining, so textbook pricing seems appropriate to me. I’m more worried whether all that profit just goes to the publishers.
oyebenny 8y ago
I'd really like to know if their Valentine's Day publishing date had a meaning.
mmcniece 8y ago
1st Edition of this book was excellent. Gives a solid explanation of both data mining/ml techniques and the trade-offs of choosing them. The update to the chapter of classification was needed. Previously, the section on SVM and ANN was a subpart of a chapter, spanning no more than 10 pages, glad they added more detail there. They also spend time in early chapters talking about preprocessing and cleaning data, something that often is glossed over.
monster_group 8y ago
I followed the first edition of this book during my master's degree Data Mining course. This is a good book (not too math heavy like [0]). It is a good book for somebody getting into data mining but it is more theoretical. For another excellent book that concentrates on building models using R I highly recommend [1] which has a great balance of theory and practical. Fun fact regarding [1] - one of the authors is the daughter of the renowned physicist Ed Witten. [0] https://web.stanford.edu/~hastie/ElemStatLearn/ https://web.stanford.edu/~hastie/ElemStatLearn/ [1] http://www-bcf.usc.edu/~gareth/ISL/ http://www-bcf.usc.edu/~gareth/ISL/

236 points by wener 8y ago

text available at http://gen.lib.rus.ec/search.php?req=introduction+to+Data+mining+ning&open=0&res=25&view=simple&phrase=0&column=def http://gen.lib.rus.ec/search.php?req=introduction+to+Data+mi...

toonervoustosay 8y ago
you're linking to an illegal ebook sharing web site this is against policy
godelmachine 8y ago
Thanks for the link :)
shawn 8y ago
Thank you.
zekrioca 8y ago
that's the 1st edition, not the 2nd as linked in the title
- shawn 8y ago
  True, but if you make the query a bit more general and sort by year, you get some wildly interesting results: http://gen.lib.rus.ec/search.php?&req=%E2%88%86introduction+to+Data+mining&phrase=0&view=simple&column=def&sort=year&sortmode=DESC http://gen.lib.rus.ec/search.php?&req=%E2%88%86introduction+...
lizhang 8y ago
Thanks!

shawn 8y ago

Great! I was just reading through the first edition this week. It's excellent. Also see Mining of Massive Datasets: http://infolab.stanford.edu/~ullman/mmds/book.pdf http://infolab.stanford.edu/~ullman/mmds/book.pdf

mark_l_watson 8y ago

Looks great. I just looked through the 3 free chapters and saved them for later reading.

blackmario 8y ago

Thanks!

Puer 8y ago

I'm excited to take this class this fall at the U of M. I've heard that the fall course is more algorithmically rigorous than the spring course because the computer science department tries to open it up to non-CS majors at that time (biology majors interested in bioinformatics, for example). The professor, George Karypis, has a reputation on campus. I'm doing a dual degree in statistical science and CS so I'm looking forward to seeing how this compares to some similar class offered by the stats department.

technofiend 8y ago

At textbook pricing this is not a casual purchase. Hopefully this is not a trend; I'd hate to see the next O'Reilly book priced north of $60.

johnsonjo 8y ago
Well I’m pretty sure it is a textbook (by Pearson a textbook publisher) put together by research PHDs in Data Mining, so textbook pricing seems appropriate to me. I’m more worried whether all that profit just goes to the publishers.

oyebenny 8y ago

I'd really like to know if their Valentine's Day publishing date had a meaning.

mmcniece 8y ago

1st Edition of this book was excellent. Gives a solid explanation of both data mining/ml techniques and the trade-offs of choosing them. The update to the chapter of classification was needed. Previously, the section on SVM and ANN was a subpart of a chapter, spanning no more than 10 pages, glad they added more detail there. They also spend time in early chapters talking about preprocessing and cleaning data, something that often is glossed over.

monster_group 8y ago

I followed the first edition of this book during my master's degree Data Mining course. This is a good book (not too math heavy like [0]). It is a good book for somebody getting into data mining but it is more theoretical. For another excellent book that concentrates on building models using R I highly recommend [1] which has a great balance of theory and practical. Fun fact regarding [1] - one of the authors is the daughter of the renowned physicist Ed Witten. [0] https://web.stanford.edu/~hastie/ElemStatLearn/ https://web.stanford.edu/~hastie/ElemStatLearn/ [1] http://www-bcf.usc.edu/~gareth/ISL/ http://www-bcf.usc.edu/~gareth/ISL/