d******a
发帖数: 15 | 1 many people think cs is easy to find a job and more difficult to learn than
statistics.
first statistics is not so easy to learn. if you learn it well, at least you
can find a teaching position in US college.
I do not think CS is more difficult to learn than Statistics.
if a person think CS is more difficult, or statisitcs is easy, that person
does not understand statistics at all.
two weeks ago, a statistics professor in our department told me that even in
usa, few statistics professors can tru | d*******o
发帖数: 493 | 2 Then what is the true basic concept of statistics? I am just curious. | b*********e
发帖数: 29 | 3 I love both.
For a CS, we need to tell a machine something.
For a stat, we need to tell people something.
The common idea for these two something is: This is a kind of "Something"
that they do not need to know at all. But, the "machine" and the "people"
always think that they can not be themselves without knowing this kind of "
something".
Agree with you at this point "few statistics professors can truly understand
the basic concept of statistics. "
As to the probability theory, how to understan | d******e
发帖数: 7844 | 4 tell machine, tell people根本没区别。
说到底都是一回事，真正关键的是看你怎么做。
看看Rutgers的Tong Zhang, CS的PhD学位，大作经常发表在AOS,JASA上。
看看Berkeley的Micheal Jordan, STAT的大牛，整天也忙着发ICML,NIPS。
我觉得Machine Learning这一块真的没什么区别，就是做是人的风格不同罢了。
understand
【在 b*********e 的大作中提到】
: I love both.
: For a CS, we need to tell a machine something.
: For a stat, we need to tell people something.
: The common idea for these two something is: This is a kind of "Something"
: that they do not need to know at all. But, the "machine" and the "people"
: always think that they can not be themselves without knowing this kind of "
: something".
: Agree with you at this point "few statistics professors can truly understand
: the basic concept of statistics. "
: As to the probability theory, how to understan
| b********p
发帖数: 875 | 5 M. Jordan严格来说不算stat的人
【在 d******e 的大作中提到】
: tell machine, tell people根本没区别。
: 说到底都是一回事，真正关键的是看你怎么做。
: 看看Rutgers的Tong Zhang, CS的PhD学位，大作经常发表在AOS,JASA上。
: 看看Berkeley的Micheal Jordan, STAT的大牛，整天也忙着发ICML,NIPS。
: 我觉得Machine Learning这一块真的没什么区别，就是做是人的风格不同罢了。
:
: understand
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