On 04/17/2013 02:43 AM, Florian Fuchs wrote:
Hi Manish, hi everyone,
2013/4/10 Manish Gill mgil...@outlook.com:
For the GSoC REST API project, I've been wondering about how
authentication would work.
OAuth is a way to go if we want authenticated/signed requests. I have a
few questions
Hi,
I am working on better user settings management for past few weeks. As i
have worked on django earlier also, so i am enjoying it.I branched out
postorius few weeks back and sent a merge request but after having
discussion with terri and florian, i now know that extension of django's
User class
for identifying an important message a classifier will be implemented. and
thanks for pointing out the issue regarding the delivery of the message, if
it is delivered twice then the existing implementation of delivery is
sufficient, but if we want to deliver it only once then for each person we
In evaluating a proposal, we need to look at a number of factors:
First, will it work? -- Does the proposed design accomplish the stated
objective?
Next: Is it useful?
And: Can the candidate be expected to accomplish the task within the allotted
time frame?
Finally: Is it the best use for our
thanks a lot for the information. Thing is that I don't think
that the Spam classifier by itself is going to be big enough so I came up
with this idea. Actually I also need to know what the community wants,
regarding the e-mail delivery. and regarding the classifier I don't think
that it
On 13-04-17 6:56 AM, Avik Pal wrote:
Meanwhile It would be much appreciated if someone can direct me to
an labeled dataset available on line.
Leaving aside entirely the question of whether we should (or will)
support any project that requires learning on this scale, as a former
On 13-04-16 10:31 PM, Stephen J. Turnbull wrote:
Pratik Sarkar writes:
I am working on the proposal.And how many slots are there for the filter
project?
There are no slots for the filter project as such. The whole Mailman
project has slots, and they are somewhat fluid, since we operate
thanks a lot Terri, I think I will go with the Enron email dataset and
they are to be cross validated against publicly available legitimate
mailing list mails and Spam and (hopefully) python's regular expressions
will help me a lot building the synthetic set.
Avik Pal
Bengal Engineering
On 17 April 2013 21:02, Terri Oda te...@zone12.com wrote:
On 13-04-17 6:56 AM, Avik Pal wrote:
Meanwhile It would be much appreciated if someone can direct
me to
an labeled dataset available on line.
Leaving aside entirely the question of whether we should (or will)
support
On 13-04-17 10:10 AM, Avik Pal wrote:
Don't lose hope Terri, after digging for a couple of hours came across
this and its pretty much updated. http://untroubled.org/spam/
Finding sources of spam (like that one) isn't that hard; it's finding
sources of legit email combined with spam and
ya I get your point, but see these are part of any machine learning
project, and feature extraction has to be done considering the synthetic
data set.
On 17 April 2013 22:05, Terri Oda te...@zone12.com wrote:
Finding sources of spam (like that one) isn't that hard; it's finding
sources of
I'm glad you're somewhat aware of the issues. I frequently encounter
folk who aren't aware of the issues in machine learning, so your don't
lose hope email set off all kinds of warning bells in my head.
Going back to GSoC-specific stuff:
- Enron is a very old data set
- If you're going to
Avik Pal writes:
Meanwhile It would be much appreciated if someone can direct me to
an labeled dataset available on line.
By labelled you mean pre-classified into spam vs ham? I see you
already found one, but you could also check the SpamBayes and
SpamAssassin distributions.
Here I have
On Apr 17, 2013, at 12:43 AM, Avik Pal wrote:
also I would like to propose an idea of my own. Many of us set the preference
in mailman to get all the emails of a day batched together, but sometimes
this means we miss important mails(though we get it at the end of the day but
we miss the
Hello !
By way of introduction I am *Adwait Sharma,* a final year computer science
undergraduate from Bangalore, India who code a lot specially in Python.
The idea I found most interesting in GSoC 2013 is Boilerplate stripper
-
Background for folk new to this discussion:
Currently, all user information is stored in Mailman core, but it's
minimal: a real name, a set of email addresses, subscription info, and
preferences. Barry suggests that it should stay minimal: only the
things Mailman needs to know to correctly
thanks a lot Stephen for all the suggestions :)
Avik Pal
Bengal Engineering Scieence University,Shibpur
github:https://github.com/avikpal
IRC:- irc://freenode/avikp,isnick
twitter:-https://twitter.com/avikpalme
On 17 April 2013 22:36, Stephen J. Turnbull step...@xemacs.org wrote:
Avik Pal
17 matches
Mail list logo
