From ramkrishna001 at gmail.com  Tue Jun  6 11:29:46 2017
From: ramkrishna001 at gmail.com (Ramkrishna P)
Date: Tue, 6 Jun 2017 20:59:46 +0530
Subject: [BangPypers] Resource for ML
Message-ID: <CAO9KM7dQyuzdR4VZ4MtGDUjUSXaRWpG_WWpZ2ji_FwYycjrJug@mail.gmail.com>

Hello Team,
I have started out to work on pandas and numpy libraries to pick some
machine learning concepts.
I feel apart from working on datasets and getting some results, the
core concepts of machine learning are still missing.

If you guys could suggest some resources, it will be of great help.


Regards,
Ramkrishna.P

From bhargav.kowshik at gmail.com  Tue Jun  6 11:42:19 2017
From: bhargav.kowshik at gmail.com (Bhargav Kowshik)
Date: Tue, 6 Jun 2017 21:12:19 +0530
Subject: [BangPypers] Resource for ML
In-Reply-To: <CAO9KM7dQyuzdR4VZ4MtGDUjUSXaRWpG_WWpZ2ji_FwYycjrJug@mail.gmail.com>
References: <CAO9KM7dQyuzdR4VZ4MtGDUjUSXaRWpG_WWpZ2ji_FwYycjrJug@mail.gmail.com>
Message-ID: <CAJNgFPi2uchoHUY0DGJFL2TXF_dXNkUd2Os+gjMbJbL97=skzA@mail.gmail.com>

Hey Ramkrishna,

I have found the following book very useful.
- https://github.com/jakevdp/PythonDataScienceHandbook

Thank you,
Bhargav

On Tue, Jun 6, 2017 at 8:59 PM, Ramkrishna P <ramkrishna001 at gmail.com>
wrote:

> Hello Team,
> I have started out to work on pandas and numpy libraries to pick some
> machine learning concepts.
> I feel apart from working on datasets and getting some results, the
> core concepts of machine learning are still missing.
>
> If you guys could suggest some resources, it will be of great help.
>
>
> Regards,
> Ramkrishna.P
> _______________________________________________
> BangPypers mailing list
> BangPypers at python.org
> https://mail.python.org/mailman/listinfo/bangpypers
>

From er.abhinav.upadhyay at gmail.com  Tue Jun  6 11:44:29 2017
From: er.abhinav.upadhyay at gmail.com (Abhinav Upadhyay)
Date: Tue, 6 Jun 2017 21:14:29 +0530
Subject: [BangPypers] Resource for ML
In-Reply-To: <CAO9KM7dQyuzdR4VZ4MtGDUjUSXaRWpG_WWpZ2ji_FwYycjrJug@mail.gmail.com>
References: <CAO9KM7dQyuzdR4VZ4MtGDUjUSXaRWpG_WWpZ2ji_FwYycjrJug@mail.gmail.com>
Message-ID: <CAHwRYJmFVp5CpkZNRJ_N0XYMt0iY1FEjMix=TdXXWFrhUVhCVg@mail.gmail.com>

On Tue, Jun 6, 2017 at 8:59 PM, Ramkrishna P <ramkrishna001 at gmail.com> wrote:
> Hello Team,
> I have started out to work on pandas and numpy libraries to pick some
> machine learning concepts.
> I feel apart from working on datasets and getting some results, the
> core concepts of machine learning are still missing.
>
> If you guys could suggest some resources, it will be of great help.

Andrew Ng's coursera course is probably the best place to start, he
covers a broad range of models which are commonly used and builds
mathematical intuitions for each of them (without bogging you down
with proofs, which have their place but not at this stage). Although,
all the programming exercises in the course use GNU Octave or Matlab.

For a slightly more in depth coverage, you may consider the University
of Washington's specialization on ML (available on Coursera). It is a
set of 4 courses. The first course is just dedicated to regression,
while the second one just covers classification models. So every
course is able to go into more details than Ng's course.  As a bonus,
all the exercises in the courses use Python.

For a more statistics oriented introduction there is a course on
Stanford Online from Trevor Hastie and Rob Tibshirani based on their
book Introduction to Statistical Learning. All the exercises use R.

PS: All the courses can be easily found with the help of Google, I
didn't have the links handy.

-
Abhinav

From gupta.harsh96 at gmail.com  Wed Jun  7 08:42:08 2017
From: gupta.harsh96 at gmail.com (Harsh Gupta)
Date: Wed, 7 Jun 2017 18:12:08 +0530
Subject: [BangPypers] Resource for ML
In-Reply-To: <CAHwRYJmFVp5CpkZNRJ_N0XYMt0iY1FEjMix=TdXXWFrhUVhCVg@mail.gmail.com>
References: <CAO9KM7dQyuzdR4VZ4MtGDUjUSXaRWpG_WWpZ2ji_FwYycjrJug@mail.gmail.com>
 <CAHwRYJmFVp5CpkZNRJ_N0XYMt0iY1FEjMix=TdXXWFrhUVhCVg@mail.gmail.com>
Message-ID: <CADN8iupvZF-OS8SX-NiZ43M7Xc8kuP=w9VBzUT+5VdazYUHObg@mail.gmail.com>

I collected some ML resources for inter hostel data analytic competition
here https://github.com/Azad-Hall/data-analytics

Other the Andrew ng's course, Caltech's "Learning from Data" (
http://work.caltech.edu/telecourse.html) course is really good for the
theoretical foundations of ML>

On 6 June 2017 at 21:14, Abhinav Upadhyay <er.abhinav.upadhyay at gmail.com>
wrote:

> On Tue, Jun 6, 2017 at 8:59 PM, Ramkrishna P <ramkrishna001 at gmail.com>
> wrote:
> > Hello Team,
> > I have started out to work on pandas and numpy libraries to pick some
> > machine learning concepts.
> > I feel apart from working on datasets and getting some results, the
> > core concepts of machine learning are still missing.
> >
> > If you guys could suggest some resources, it will be of great help.
>
> Andrew Ng's coursera course is probably the best place to start, he
> covers a broad range of models which are commonly used and builds
> mathematical intuitions for each of them (without bogging you down
> with proofs, which have their place but not at this stage). Although,
> all the programming exercises in the course use GNU Octave or Matlab.
>
> For a slightly more in depth coverage, you may consider the University
> of Washington's specialization on ML (available on Coursera). It is a
> set of 4 courses. The first course is just dedicated to regression,
> while the second one just covers classification models. So every
> course is able to go into more details than Ng's course.  As a bonus,
> all the exercises in the courses use Python.
>
> For a more statistics oriented introduction there is a course on
> Stanford Online from Trevor Hastie and Rob Tibshirani based on their
> book Introduction to Statistical Learning. All the exercises use R.
>
> PS: All the courses can be easily found with the help of Google, I
> didn't have the links handy.
>
> -
> Abhinav
> _______________________________________________
> BangPypers mailing list
> BangPypers at python.org
> https://mail.python.org/mailman/listinfo/bangpypers
>



-- 
Harsh
Sent from a GNU/Linux

From rajvidhimar95 at gmail.com  Wed Jun  7 09:23:15 2017
From: rajvidhimar95 at gmail.com (Rajvi Dhimar)
Date: Wed, 7 Jun 2017 18:53:15 +0530
Subject: [BangPypers] Query regarding packages in PyPI.
Message-ID: <CA+5Wa=E1YjSMPw_7i59nfH7GXf101OK8MQo0Soxdzg-M5MJY7Q@mail.gmail.com>

Hello experts,

I am trying to get certain packages from pypi onto a network device. On the
device I cannot do a 'pip install'.
I need to write a shell scripy to fetch the package (using curl or fetch
command) from PyPI on to my network device.

Earlier, the packages were located at
https://pypi.python.org/packages/source. Suppose I want the tar of v1.0.0
of package abc,
I could do it via the following command:
     *fetch https://pypi.python.org/packages/source/A/abc/abc-1.0.0
<https://pypi.python.org/packages/source/A/abc/abc-1.0.0>.tar.gz*

Now I see that the packages are present at: *https://pypi.python.org/simple/
<https://pypi.python.org/simple/>.*
Eg: All the abc packages would be at *https://pypi.python.org/simple/abc
<https://pypi.python.org/simple/abc>*
But a specific package link looks something like:

*
https://pypi.python.org/packages/33/db/9931c645626f9bf77ecddb7e7d5df90a3b6c4/abc-1.0.0.tar.gz
<https://pypi.python.org/packages/33/db/9931c645626f9bf77ecddb7e7d5df90a3b6c4/abc-1.0.0.tar.gz>*

The link as we see, won't be uniform across packages as there is a dynamic
database ID kind of thing in the link.
Beacuse I am trying to download a huge number of packages via the same
shell script, I need a generic path where
the packages are in PyPI. Does anyone know, where the PyPI packages are
hosted?

Thanks,
Rajvi Dhimar

From npropadovic at gmail.com  Wed Jun  7 09:40:31 2017
From: npropadovic at gmail.com (Propadovic Nenad)
Date: Wed, 7 Jun 2017 15:40:31 +0200
Subject: [BangPypers] Resource for ML
In-Reply-To: <CAHwRYJmFVp5CpkZNRJ_N0XYMt0iY1FEjMix=TdXXWFrhUVhCVg@mail.gmail.com>
References: <CAO9KM7dQyuzdR4VZ4MtGDUjUSXaRWpG_WWpZ2ji_FwYycjrJug@mail.gmail.com>
 <CAHwRYJmFVp5CpkZNRJ_N0XYMt0iY1FEjMix=TdXXWFrhUVhCVg@mail.gmail.com>
Message-ID: <CAD0yHOyLHBVH-XJmd60yYuRuLZ9G6h_=ODKjvtY8M4JQ6=ceFQ@mail.gmail.com>

Hello,
while not having finished Andrew Ng's coursera course (yet), I started it
and like it, too. I don't think it's an disadvantage that it's Matlab (or
it's open source counterpart, Octave) - based (and I'm much more proficient
in Python than in Matlab).
Thanks to Abhinav and Harsh for the other recommendations.
Cheers,
Nenad

2017-06-06 17:44 GMT+02:00 Abhinav Upadhyay <er.abhinav.upadhyay at gmail.com>:

> On Tue, Jun 6, 2017 at 8:59 PM, Ramkrishna P <ramkrishna001 at gmail.com>
> wrote:
> > Hello Team,
> > I have started out to work on pandas and numpy libraries to pick some
> > machine learning concepts.
> > I feel apart from working on datasets and getting some results, the
> > core concepts of machine learning are still missing.
> >
> > If you guys could suggest some resources, it will be of great help.
>
> Andrew Ng's coursera course is probably the best place to start, he
> covers a broad range of models which are commonly used and builds
> mathematical intuitions for each of them (without bogging you down
> with proofs, which have their place but not at this stage). Although,
> all the programming exercises in the course use GNU Octave or Matlab.
>
> For a slightly more in depth coverage, you may consider the University
> of Washington's specialization on ML (available on Coursera). It is a
> set of 4 courses. The first course is just dedicated to regression,
> while the second one just covers classification models. So every
> course is able to go into more details than Ng's course.  As a bonus,
> all the exercises in the courses use Python.
>
> For a more statistics oriented introduction there is a course on
> Stanford Online from Trevor Hastie and Rob Tibshirani based on their
> book Introduction to Statistical Learning. All the exercises use R.
>
> PS: All the courses can be easily found with the help of Google, I
> didn't have the links handy.
>
> -
> Abhinav
> _______________________________________________
> BangPypers mailing list
> BangPypers at python.org
> https://mail.python.org/mailman/listinfo/bangpypers
>

From gupta.harsh96 at gmail.com  Wed Jun  7 10:05:43 2017
From: gupta.harsh96 at gmail.com (Harsh Gupta)
Date: Wed, 7 Jun 2017 19:35:43 +0530
Subject: [BangPypers] Query regarding packages in PyPI.
In-Reply-To: <CA+5Wa=E1YjSMPw_7i59nfH7GXf101OK8MQo0Soxdzg-M5MJY7Q@mail.gmail.com>
References: <CA+5Wa=E1YjSMPw_7i59nfH7GXf101OK8MQo0Soxdzg-M5MJY7Q@mail.gmail.com>
Message-ID: <CADN8iuqqL7DSsX1pMvznMBshsdjwMZBMOhTND_QBiYeoXiqA5Q@mail.gmail.com>

If you are want download a lot of packages and can't do pip install, you
can try creating a local mirror of PyPI. You can use the following tools
for that:

* Bandersnatch https://bitbucket.org/pypa/bandersnatch
* DevPi http://doc.devpi.net/latest/


On 7 June 2017 at 18:53, Rajvi Dhimar <rajvidhimar95 at gmail.com> wrote:

> Hello experts,
>
> I am trying to get certain packages from pypi onto a network device. On the
> device I cannot do a 'pip install'.
> I need to write a shell scripy to fetch the package (using curl or fetch
> command) from PyPI on to my network device.
>
> Earlier, the packages were located at
> https://pypi.python.org/packages/source. Suppose I want the tar of v1.0.0
> of package abc,
> I could do it via the following command:
>      *fetch https://pypi.python.org/packages/source/A/abc/abc-1.0.0
> <https://pypi.python.org/packages/source/A/abc/abc-1.0.0>.tar.gz*
>
> Now I see that the packages are present at: *https://pypi.python.org/simpl
> e/
> <https://pypi.python.org/simple/>.*
> Eg: All the abc packages would be at *https://pypi.python.org/simple/abc
> <https://pypi.python.org/simple/abc>*
> But a specific package link looks something like:
>
> *
> https://pypi.python.org/packages/33/db/9931c645626f9bf77ecdd
> b7e7d5df90a3b6c4/abc-1.0.0.tar.gz
> <https://pypi.python.org/packages/33/db/9931c645626f9bf77ecd
> db7e7d5df90a3b6c4/abc-1.0.0.tar.gz>*
>
> The link as we see, won't be uniform across packages as there is a dynamic
> database ID kind of thing in the link.
> Beacuse I am trying to download a huge number of packages via the same
> shell script, I need a generic path where
> the packages are in PyPI. Does anyone know, where the PyPI packages are
> hosted?
>
> Thanks,
> Rajvi Dhimar
> _______________________________________________
> BangPypers mailing list
> BangPypers at python.org
> https://mail.python.org/mailman/listinfo/bangpypers
>



-- 
Harsh
Sent from a GNU/Linux

From anandology at gmail.com  Wed Jun  7 10:11:23 2017
From: anandology at gmail.com (Anand Chitipothu)
Date: Wed, 7 Jun 2017 19:41:23 +0530
Subject: [BangPypers] Resource for ML
In-Reply-To: <CAO9KM7dQyuzdR4VZ4MtGDUjUSXaRWpG_WWpZ2ji_FwYycjrJug@mail.gmail.com>
References: <CAO9KM7dQyuzdR4VZ4MtGDUjUSXaRWpG_WWpZ2ji_FwYycjrJug@mail.gmail.com>
Message-ID: <CAC7wXFwbR97cRJi_nT7LkJg_P=L9QcicEQFGvbxrMV7kxY06Hg@mail.gmail.com>

On Tue, Jun 6, 2017 at 8:59 PM, Ramkrishna P <ramkrishna001 at gmail.com>
wrote:

> Hello Team,
> I have started out to work on pandas and numpy libraries to pick some
> machine learning concepts.
> I feel apart from working on datasets and getting some results, the
> core concepts of machine learning are still missing.
>
> If you guys could suggest some resources, it will be of great help.
>

I find Learn Data Science very good place to start, esp. for the beginners.

http://learnds.com/

Anand

From arjunil.pathak at gmail.com  Wed Jun  7 10:25:51 2017
From: arjunil.pathak at gmail.com (Arjunil Pathak)
Date: Wed, 7 Jun 2017 19:55:51 +0530
Subject: [BangPypers] Resource for ML
In-Reply-To: <CAC7wXFwbR97cRJi_nT7LkJg_P=L9QcicEQFGvbxrMV7kxY06Hg@mail.gmail.com>
References: <CAO9KM7dQyuzdR4VZ4MtGDUjUSXaRWpG_WWpZ2ji_FwYycjrJug@mail.gmail.com>
 <CAC7wXFwbR97cRJi_nT7LkJg_P=L9QcicEQFGvbxrMV7kxY06Hg@mail.gmail.com>
Message-ID: <CAPSF14YTbp+55kFVNSqYpSXH7+QmaZ5hydFPqTz0cXixQjL43g@mail.gmail.com>

I can vouch for Coursera's ML courses by University of Washington.

It gives you a brief overview of the possibilities ML presents in the
foundations course - predictive models using regression,  document
classification, recommender systems in the very first course - good for
whetting your appetite with a black box approach. The next courses delve
deep into each example, be it Regression, or Classification - with generous
doses of math(some of it optional).
They use jupyter notebooks and have adapted to present solutions in
scikit-learn apart from the proprietary stuff they initially started off
with because one of the instructors was a founder of an AI and ML start-up
that they tried promoting  ( Maybe you've heard of Dato, now goes by the
name of Turi - acquired by Apple).

It should give you a good, firm grasp on the basics and enough to keep you
busy for a while.

On Wed, Jun 7, 2017 at 7:41 PM, Anand Chitipothu <anandology at gmail.com>
wrote:

> On Tue, Jun 6, 2017 at 8:59 PM, Ramkrishna P <ramkrishna001 at gmail.com>
> wrote:
>
> > Hello Team,
> > I have started out to work on pandas and numpy libraries to pick some
> > machine learning concepts.
> > I feel apart from working on datasets and getting some results, the
> > core concepts of machine learning are still missing.
> >
> > If you guys could suggest some resources, it will be of great help.
> >
>
> I find Learn Data Science very good place to start, esp. for the beginners.
>
> http://learnds.com/
>
> Anand
> _______________________________________________
> BangPypers mailing list
> BangPypers at python.org
> https://mail.python.org/mailman/listinfo/bangpypers
>



-- 
Arjunil Pathak

From rus.cahimb at gmail.com  Sun Jun 11 02:47:34 2017
From: rus.cahimb at gmail.com (Ramanathan Muthaiah)
Date: Sun, 11 Jun 2017 06:47:34 +0000
Subject: [BangPypers] [Meetup] RSVP is open June meetup
Message-ID: <CAGBd0eq+zBe+=epJ4BdzMJqJqkYT1BVCteb3mKeCNbgfbu_ZPQ@mail.gmail.com>

Hi

RSVP for June month meetup is open. There are four talks confirmed.

These talks are continuation of previous (May) meetup's theme -- "The
Journey to the Kernel".

1. Multidimensional data is just an abstraction over the linearly stored
data in memory. This talk is about understanding how the two main types of
memory layouts and their effect on the performance of the code by Sarah
2. "Generators under the hood" by Shaifali Agarwal
3. How the interpreter works from the source code by Prashanth Raghu
4. Application of meta-programming and meta-classes in example Python
library/framework by Vishal Yadav

The complete details are available on the meetup page [0].

You can RSVP on the meetup page [0].

Google Map: https://goo.gl/maps/4FgAJw7qMVR2

The event is free of cost.

[0]: *https://www.meetup.com/BangPypers/events/239426318/
<https://www.meetup.com/BangPypers/events/239426318/>*

--
Thanks & Regards
Ramanathan.M
_______________________________________________
BangPypers mailing list
BangPypers at python.org
https://mail.python.org/mailman/listinfo/bangpypers

From abhasbhattacharya2 at gmail.com  Sun Jun 11 09:40:20 2017
From: abhasbhattacharya2 at gmail.com (Abhas Bhattacharya)
Date: Sun, 11 Jun 2017 19:10:20 +0530
Subject: [BangPypers] Query regarding packages in PyPI.
In-Reply-To: <CADN8iuqqL7DSsX1pMvznMBshsdjwMZBMOhTND_QBiYeoXiqA5Q@mail.gmail.com>
References: <CA+5Wa=E1YjSMPw_7i59nfH7GXf101OK8MQo0Soxdzg-M5MJY7Q@mail.gmail.com>
 <CADN8iuqqL7DSsX1pMvznMBshsdjwMZBMOhTND_QBiYeoXiqA5Q@mail.gmail.com>
Message-ID: <CAC5tdwOrKF5gmYOFipw0yRs2xRKeiqxpVKyRXEyOkb6BZG0NAw@mail.gmail.com>

Or you can do something like create a list of all the dependencies
(recursively) of all the packages and then use pip to only fetch/download
all those packages.

Later you can take all those files and pip install them from the local
folder. You can do something like pip path/packagename.tar.gz to install it
locally.
For creating the list of dependencies I am sure there is something like
that available as a module or part of pip cmdline options.
As for zipped folder download for pypi packages, I think you are going to
have a hard time nowadays because you can upload them in many formats like
tar, wheel, zip and some others as a package maintainer and usually people
upload multiple of those. This exact package is then resolved according to
your platform and python version. So, its a lot of work to do by yourself.
Better let pip handle it.

I am sure you'll find an easy standard solution to this if you go along
these lines. Please share your findings in the end.

On Jun 7, 2017 7:36 PM, "Harsh Gupta" <gupta.harsh96 at gmail.com> wrote:

> If you are want download a lot of packages and can't do pip install, you
> can try creating a local mirror of PyPI. You can use the following tools
> for that:
>
> * Bandersnatch https://bitbucket.org/pypa/bandersnatch
> * DevPi http://doc.devpi.net/latest/
>
>
> On 7 June 2017 at 18:53, Rajvi Dhimar <rajvidhimar95 at gmail.com> wrote:
>
> > Hello experts,
> >
> > I am trying to get certain packages from pypi onto a network device. On
> the
> > device I cannot do a 'pip install'.
> > I need to write a shell scripy to fetch the package (using curl or fetch
> > command) from PyPI on to my network device.
> >
> > Earlier, the packages were located at
> > https://pypi.python.org/packages/source. Suppose I want the tar of
> v1.0.0
> > of package abc,
> > I could do it via the following command:
> >      *fetch https://pypi.python.org/packages/source/A/abc/abc-1.0.0
> > <https://pypi.python.org/packages/source/A/abc/abc-1.0.0>.tar.gz*
> >
> > Now I see that the packages are present at: *
> https://pypi.python.org/simpl
> > e/
> > <https://pypi.python.org/simple/>.*
> > Eg: All the abc packages would be at *https://pypi.python.org/simple/abc
> > <https://pypi.python.org/simple/abc>*
> > But a specific package link looks something like:
> >
> > *
> > https://pypi.python.org/packages/33/db/9931c645626f9bf77ecdd
> > b7e7d5df90a3b6c4/abc-1.0.0.tar.gz
> > <https://pypi.python.org/packages/33/db/9931c645626f9bf77ecd
> > db7e7d5df90a3b6c4/abc-1.0.0.tar.gz>*
> >
> > The link as we see, won't be uniform across packages as there is a
> dynamic
> > database ID kind of thing in the link.
> > Beacuse I am trying to download a huge number of packages via the same
> > shell script, I need a generic path where
> > the packages are in PyPI. Does anyone know, where the PyPI packages are
> > hosted?
> >
> > Thanks,
> > Rajvi Dhimar
> > _______________________________________________
> > BangPypers mailing list
> > BangPypers at python.org
> > https://mail.python.org/mailman/listinfo/bangpypers
> >
>
>
>
> --
> Harsh
> Sent from a GNU/Linux
> _______________________________________________
> BangPypers mailing list
> BangPypers at python.org
> https://mail.python.org/mailman/listinfo/bangpypers
>

From sayan.chowdhury2012 at gmail.com  Sun Jun 11 11:04:55 2017
From: sayan.chowdhury2012 at gmail.com (Sayan Chowdhury)
Date: Sun, 11 Jun 2017 20:34:55 +0530
Subject: [BangPypers] [XPOST] A new Mailing List for PyCon Pune
Message-ID: <CAHPYoWS37znh0fz-je5tYftVY3vuvXXA_igu0Nz-HXJYSoEzDw@mail.gmail.com>

Hi,

PyCon Pune 2017 was a grand success. Now, its time to set the tune for
PyCon Pune 2018.

Since our first endeavor it has always been a community driven event
and we wish to be so. To give a shape to our 2018 edition we, the
community at large, need to communicate. Now we have a new space for
discussion, the PyCon Pune mailing list[1]. All the conversation,
exchange of ideas related to our 2018 and also for all our future
editions will be happening here. Everyone is welcome to join.

Together lets make the dream of a triumphant PyCon Pune 2018 a shining truth.

[1] https://mail.python.org/mailman/listinfo/pycon-pune


-- 
Sayan Chowdhury <https://sayanchowdhury.dgplug.org/>
Senior Software Engineer, Fedora Engineering - Emerging Platform
GPG Fingerprint : 0F16 E841 E517 225C 7D13  AB3C B023 9931 9CD0 5C8B


Proud to work at The Open Organization!

From saloni.s at byteacademy.co  Mon Jun 19 10:45:03 2017
From: saloni.s at byteacademy.co (Saloni Samant)
Date: Mon, 19 Jun 2017 20:15:03 +0530
Subject: [BangPypers] [Commercial] Python and Data Science Bootcamp in
 Bangalore
Message-ID: <C4B05897-8EE4-4571-BC68-25184C75DBD6@byteacademy.co>

Hi all,

We have hosted a BangPypers event in the past and had promised information about our upcoming courses in Bangalore.

To recap, Byte Academy is a New York- based Academy that conducts short immersive courses in FullStack Python and Data Science. We are happy to give all members of the BangPypers group 15% off our full course fees. 

More information about the courses: 

Data Science:
Arguably the most comprehensive curriculum on offer in India, Byte?s Data Science course covers topics including data acquisition, data analysis, Pandas, prediction and machine learning, statistical modeling, Hadoop, SQL, NoSQL and more. Graduates go into roles such as Data Scientist, Data Analyst, Data Engineer and Data Architect after the program. The course uses Python to learn and apply the data science concepts. Candidates do not need any prior data science experience. Students are expected to complete a minimum of 2 projects by the end of the course. You can find more information at http://byteacademy.co/courses/data-science <http://byteacademy.co/courses/data-science>

Full-Stack Python
Our Python Full-stack Python course teaches languages, frameworks, and computer science fundamentals that is needed to land a career in web development over a 12 (full-time) period. The curriculum emphasizes Python, a coding language based on the foundational structure of networked programming. It provides instruction in other front and backend languages including JavaScript, HTML/HTML5, CSS/CSS3. Byte Academy aims to simulate a job environments in its classes and thus has heavy focus on teamwork, peer programming and project building (which can then be showcased to prospective employers to demonstrate their job-readiness). More information at http://byteacademy.co/courses/python <http://byteacademy.co/courses/python>

Both courses are offered in Full-Time and Part-Time options. The Full-Time option runs Monday - Friday 10am to 6pm for 3 months.
The Part-Time course runs on Tuesday and Thursday 6pm to 9pm and Saturday 10am to 6pm for 6 months. 

The next cohort for both courses begins on 10th July and the application deadline is  23rd June, 11:59am. 

Please do not hesitate to reach out to me if you have any questions or need any more information.


Best,
Saloni Samant
Byte Academy
+91 7760494717






From dtu.amit at gmail.com  Tue Jun 20 12:19:54 2017
From: dtu.amit at gmail.com (Amit Kumar)
Date: Tue, 20 Jun 2017 21:49:54 +0530
Subject: [BangPypers] [XPOST] PyDelhi Meetup on 24th June, 2017
Message-ID: <CAKtu8vUq5jF0E=fhecO26uFLmGm9kpV9N0mW=_8niryoS1GA=w@mail.gmail.com>

Hi,

The next PyDelhi Meetup is scheduled for this Saturday, 24th June, 2017.
Below is the schedule for the same.

Schedule
------------

11:00 - 12:00: Introductions

12:00 - 1:00:  Make Telegram Bot Using Python And Run On Your Phone

by Shashank Kumar

He will be covering the use of telegram bot API from scratch.

? Telegram Bot API
? Making request and sending response to Bot
? Using Telegram-Python-Bot package
? Deploying bot on your smartphone
? Other options to deploy

1:15 - 2:15: Ethereum Blockchain by Amit Kumar Jaiswal

Amit Kumar Jaiswal is an open hacktivist and a Mozilla Representative. The
community is everything that matter to him, Loves to give talks and
sessions varying from Programming stuff to Community Ideas.

He is also a Google Summer of Code 2017 Student at Cloud Native Computing
Foundation

2:15 - 3:00: Networking & Tea/Snacks

3:00 - 4:00: Hiring, Pitching, Lightning Talks

4:00 - 5:00: PyCon India 2017 Discussion

NOTE: Please bring a valid Identity Card to get entry into the office.
Entry would not be allowed without a valid identity card.

-----------------------------


All those who have already volunteered and would like to volunteer to make
this local user group bigger and stronger should stay back.

Note:

1. This is a bi-weekly meetup that happens every alternate Saturday, so if
are not able to make it to this one, catch up with us in the next one.

2. This event is completely free and volunteer driven, please feel free to
contribute.

Contact Person:

Amit Kumar: +91 9811522423
Akshay Arora: +91 9013159973

Venue: Awaiting confirmation (Will be notified soon).

RSVP here: https://www.meetup.com/pydelhi/events/238176680/

Regards,
Amit Kumar
(http://iamit.in)
?

?

From abhi.darkness at gmail.com  Tue Jun 20 15:48:10 2017
From: abhi.darkness at gmail.com (abhi.darkness at gmail.com)
Date: Tue, 20 Jun 2017 19:48:10 +0000
Subject: [BangPypers] [Bangpypers] WebCast Details Survey
Message-ID: <001a1139c44004512905526988d8@google.com>

I've invited you to fill out the following form:
Webcast details survey

To fill it out, visit:
https://docs.google.com/forms/d/e/1FAIpQLSdr2CJQx7yAiKm0QmMIUHdQyQTZ0holI9xRV4Vd3l9R17VCiQ/viewform?c=0&amp;w=1&amp;usp=mail_form_link

Hi, please fill in this short survey with your opinions and suggestions so  
we can take a unanimous decision about how to set up the forthcoming  
Webcast series.

Thanks
Abhiram

Google Forms: Create and analyze surveys.

From anand21nanda at gmail.com  Wed Jun 21 01:14:35 2017
From: anand21nanda at gmail.com (Chillar Anand)
Date: Wed, 21 Jun 2017 10:44:35 +0530
Subject: [BangPypers] [Meetup] Machine Learning & Deep Learning Talks
Message-ID: <CALCtiO5YoSdjFc30jomg5OXnWWBUXsXuPAguCue9JJhrS1BmrA@mail.gmail.com>

Hi,

For the next 3 months, we are planning to have talks about machine learning
and deep learning.

For the first month i.e., July, we will have talks about fundamentals and
building
blocks of machine learning.

You are welcome to talk about basic topics like calculus with Python,
basics of Neural Networks, Bayesian probability and statistics with Python,
Linear regression, gradient descent etc.

If you are planning to give talks about specific tools like TensorFlow,
Theano e.t.c.,
or specific class of neural networks like Convolutional Neural Networks,
Recurrent
Neural Networks e.t.c., or about GPU programming, you can talk about it
in the upcoming meetups i.e., August or September.

If you need further information or if you are interested in giving a talk,
please leave a comment on the meetup page[1].

If you are giving a talk and if you expect audience to know about specific
topics,
please mention them as pre-requisites so that people will come prepared for
the talk.


[1]: https://www.meetup.com/BangPypers/events/240151299/


Regards,
Chillar Anand
avilpage.com

From gulsumramazanoglu at gmail.com  Fri Jun 23 03:56:42 2017
From: gulsumramazanoglu at gmail.com (Gugu Rama)
Date: Fri, 23 Jun 2017 10:56:42 +0300
Subject: [BangPypers] To connect to a remote DB2(AS400) over Python,
 in any case do we have to pay to IBM for the driver?
Message-ID: <CAG2jv3fALPcvTsr8gYZbDigz-REjGufk6UsQUMtSipdbYRpcJQ@mail.gmail.com>

Hi everybody,

I am new here and have a question, if you can help I will be really
happy...

To connect to a DB2 of a remote AS400 over any one of the Python DB API
interfaces (ibm_db, pyodbc, pyDB2 or any other one) from Python on
Windows10, do we in any case have to use IBMs proprietary ODBC driver
(which demands at the last point of connection a licence key which has a
good price)?  In other words, is there any non-proprietary way of
connecting to a remote iseries? If not, there is no point in discussing or
investing in iseries communication, my decision will be to put AS400 as a
whole in garbage and move on with other RDBMSs.


Thank you in advance..

Gulsum

From arvindpdmn at gmail.com  Sun Jun 25 10:55:53 2017
From: arvindpdmn at gmail.com (Arvind Padmanabhan)
Date: Sun, 25 Jun 2017 20:25:53 +0530
Subject: [BangPypers] Talk: Python Pitfalls and Best Practices
Message-ID: <CAFF8NCjkWPFHy4yxLqwsY9FNJzEGWUmV0Nd_OrHjL+Yq2578fA@mail.gmail.com>

Hi BangPypers,


*Theme: Python Pitfalls and Best Practices*


*When: Wednesday, 28th June, 5.30 PM - 7.00 PM*


*Where: BHIVE Residency Road*
*Register On Meetup.com: https://www.meetup.com/Devopedia/events/241018875/
<https://www.meetup.com/Devopedia/events/241018875/>*

So, you've been programming in Python for sometime but are not sure if
you're using the language correctly. Programmers coming from C, Java or
perl might use Python in less efficient ways that how it's meant to be
used. This talk will help you iron out those wrinkles and make you a better
Python programmer.

We will show some pitfalls and then share best practices for programming in
Python.

This talk is for beginners and intermediate Python programmers. It's not
ideal for someone completely new to Python but you can probably pick up a
few things to get started in Python.

Regards,
Arvind Padmanabhan