http://mail.python.org/pipermail/python-list/2011-May/127258...
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is the link which is in the same conversation [which includes quora link you posted , the python ,the pearl and the comparison in the finest print i ve come across],but yes it takes patience to get that.
a very very interesting tagline.
out of honest curiosity
it occurred to me that tagline of this blog can mean many things:
tagline:
me = entrepreneur + hacker
also implies
me - entrepreneur = hacker
me - hacker = entrepreneur
do you agree that all three meaning are consistent to your context?
I could not ignore the question,Despite knowing that wave of semantic web/action knowledge discovery/connected knowledge/domain driven data mining is yet to arrive
Your inputs requested
I am trying to tweak this post in an attempt to explain finite state automation in layman terms using comics.
Posting at HN is intended for suggestions.
regrets for delay in explanation
1. It ll have n+1 sheets ..
2. Like a 3d periodic table for methods
3. every step begins with a new row every block of which in a diff column will contain a symbol/operator/number etc.
4. first n sheets will contain n methods to solve problem x,with n*m(i) error functions .[m(i) number of steps in ith)
5. n sheets will be connected semantically and contextually optimized
6. combinations of steps.
7. on n+1 th sheet user feeds his problem ,
8. If the context is matched,he is asked to feed his method steps to
solve the problem on the RHS of the n+1 th sheet he gets validity/proof
of his steps and recommended steps for optimized error in terms of
contextual tolerance
9. #example spreadsheet
https://spreadsheets.google.com/...
assume that recommender is added to this sheet's back-end
Look at this sheet
now if i want to make a new sheet to strategize say my academics
and start feeding parameters to this new sheet
[switch to listview of spreadsheet]
when i click a drop down in list view i ll see the recommended data formula to feed with it's row*column location.
10. I find it related to structured prediction
11. #use case
12. think of toy design or drug formulation companies.
##They have vast unorganized history{across past aand organization} of methododologies and results ##
which can be converted to methodbase ,
just as documents s are converted to knowledge base using machine learning semantics .
this method-base is comparable to the old sheets on the example spreadsheet i messaged you earlier......
The
charles sheet on the spreadhseet was comparable to GUI of the product
where the drug formulator /toy designer feeds his objective and blocks
of procedure( steps of solution ,methods, images etc }
this gets compared with what is recorded on old sheets[method-base]
and
on the RHS of Charles sheet recommended steps /methods appear such that
noise/signal ,learning curve,resource stress ,risk and error count is
mitgiated .
Honestly my time frame = stay as long as it takes. I could move within a couple of weeks if the opportunity is right. My plan is to be there for at least 10-12 months.