<div dir="ltr">@sairam, you can get the presentations from the meetup page (chennaipy <a href="http://meetup.com">meetup.com</a>)</div><div class="gmail_extra"><br><div class="gmail_quote">On 30 August 2016 at 11:08, Sairam Murali <span dir="ltr"><<a href="mailto:isairamm@gmail.com" target="_blank">isairamm@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Hi All,<div><br></div><div>Went through the meeting notes, it would be great if there is a place where can i get the presentation or recordings of the talks?</div><div><br></div><div>Thanks!</div><div>Sai</div></div><div class="gmail_extra"><br><div class="gmail_quote">On Mon, Aug 29, 2016 at 4:13 PM, <span dir="ltr"><<a href="mailto:chennaipy-request@python.org" target="_blank">chennaipy-request@python.org</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Send Chennaipy mailing list submissions to<br>
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1. Re: August Meetup - Minutes (hafizul azeez)<br>
<br>
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<br>
Message: 1<br>
Date: Mon, 29 Aug 2016 16:13:31 +0530<br>
From: hafizul azeez <<a href="mailto:hafizul.azeez@gmail.com" target="_blank">hafizul.azeez@gmail.com</a>><br>
To: Chennai Python User Group Mailing List <<a href="mailto:chennaipy@python.org" target="_blank">chennaipy@python.org</a>><br>
Subject: Re: [Chennaipy] August Meetup - Minutes<br>
Message-ID:<br>
<<a href="mailto:CAAAE1MpFJjB3t3m6fKrBn2qkd30o8RWnV4SH-y%2B1MBA-_-pT%2BA@mail.gmail.com" target="_blank">CAAAE1MpFJjB3t3m6fKrBn2qkd30o<wbr>8RWnV4SH-y+1MBA-_-pT+A@mail.gm<wbr>ail.com</a>><br>
Content-Type: text/plain; charset="utf-8"<br>
<br>
Anand,<br>
<br>
It's easily doable. You can use Flask web framework to do it. You can send<br>
a request via ajax from the client (browser) to the server with the input<br>
being a random number between 1 and 100 (or the max number of quotes) you<br>
have in your db or for that matter in a text file.<br>
<br>
The server takes the request, checks the paramater (the random number) and<br>
picks the appropriate row id from the database and return it as json or as<br>
a python object which you can format (using jinja templates) and write to<br>
the DOM of the browser.<br>
<br>
I suggest you start with a Flask tutorial - which will give you a general<br>
idea :<br>
<a href="http://code.tutsplus.com/tutorials/creating-a-web-app-from-scratch-using-python-flask-and-mysql--cms-22972" rel="noreferrer" target="_blank">http://code.tutsplus.com/tutor<wbr>ials/creating-a-web-app-from-<wbr>scratch-using-python-flask-<wbr>and-mysql--cms-22972</a><br>
<br>
<br>
Thanks<br>
Azeez<br>
<br>
On 29 August 2016 at 15:59, Anand Surampudi <<a href="mailto:asinode@zoho.com" target="_blank">asinode@zoho.com</a>> wrote:<br>
<br>
> Sure Azeeze. I will work on that. Thanks for your constant push.<br>
><br>
> Meanwhile, can you or anybody suggest a resource for learning how to<br>
> achieve a small task in python. What I want to do is to build a web page<br>
> that randomly generates a quote on every click of a button. Lets just say I<br>
> want to host this page on github pages. I know how content-based github<br>
> pages work since I maintain my blog there. But this is something I want to<br>
> learn using github pages and python. This is it.<br>
><br>
> I am sure this sounds pretty silly. But as a beginner, I would like to<br>
> give myself this kind of tasks for my learning.<br>
><br>
> On script level, I can do it. I mean I run the script on terminal and it<br>
> definitely throws the random quote as an output. But I want the same thing<br>
> to happen on a web page, but random printing should happen on every click<br>
> of a button, say something like, "Surprise me!" or something.<br>
><br>
> Thanks.<br>
> Anand<br>
><br>
> On Mon, Aug 29, 2016 at 2:50 PM, hafizul azeez <<a href="mailto:hafizul.azeez@gmail.com" target="_blank">hafizul.azeez@gmail.com</a>><br>
> wrote:<br>
><br>
>> Anand,<br>
>><br>
>> Hope you are getting well now!<br>
>><br>
>> I gave my first talk (ah.. finally) after 3 meetups - though it was<br>
>> unprepared. I encourage you to do the talks sometime. We would love to hear<br>
>> from you - your thoughts and experiments with python.<br>
>><br>
>> Azeez<br>
>><br>
>><br>
>> On 29 August 2016 at 14:31, Anand Surampudi <<a href="mailto:asinode@zoho.com" target="_blank">asinode@zoho.com</a>> wrote:<br>
>><br>
>>> Azeez,<br>
>>><br>
>>> You really made me feel so bad. You forced me to see how much I missed.<br>
>>> Just kidding! ;-)<br>
>>><br>
>>> But from your minutes, I seriously regret not making it yesterday as I<br>
>>> was down with fever. That was very elaborate record of minutes and thanks a<br>
>>> lot for initiating this. I will try to make use of the material that is<br>
>>> hopefully going on github soon.<br>
>>><br>
>>> Anand<br>
>>><br>
>>> On Mon, Aug 29, 2016 at 10:57 AM, hafizul azeez <<a href="mailto:hafizul.azeez@gmail.com" target="_blank">hafizul.azeez@gmail.com</a><br>
>>> > wrote:<br>
>>><br>
>>>> The non-stop drizzle, the quiet IMSc environment and vibrant<br>
>>>> pythonistas set the context and expectations for the August meetup.<br>
>>>> However, plans took unexpected turns when the speakers got delayed due to<br>
>>>> the drizzling rain outside and the traffic created by it. Vijay took the<br>
>>>> stage to engage the audience with round of introductions and a generic Q&A<br>
>>>> session on python and the community. All of them took the opportunity to<br>
>>>> introduce themselves and a few asked some interesting questions. With the<br>
>>>> speakers not turning up yet, Vijay announced a lightning talk session.<br>
>>>><br>
>>>> Rengaraj from Zilogic systems took the opportunity to present an idea<br>
>>>> he was working with (DBus), explained the design and asked for feedback and<br>
>>>> contributions. Kudos to Rengaraj - though it was a lighting talk, taking to<br>
>>>> the stage with no slides and preparation within few minutes summons respect<br>
>>>> and appreciation.<br>
>>>><br>
>>>> An introduction to Flask by Hafizul Azeez<br>
>>>><br>
>>>> As an emergency talk, Azeez gave a brief description of Flask and how<br>
>>>> it can be used for rapid application development. Azeez highlighted the<br>
>>>> difference between the micro web framework, Flask and how it is compared<br>
>>>> with a batteries included framework like Django. He gave a brief demo of<br>
>>>> how a simple Flask web app looks like and explained the code behind the app.<br>
>>>><br>
>>>> He also made slight changes to the code with the inclusion of html<br>
>>>> templates and how parameters can be passed from the client side to the<br>
>>>> server side thru Flask routes a.k.a end points. In the process, he said how<br>
>>>> the Flask framework supports a design pattern called MVT (Models, Views and<br>
>>>> Templates) and how it all works in orchestration to make the web app.<br>
>>>><br>
>>>> He also gave additional inputs on extending the Flask app with Plugins<br>
>>>> and highlighted a few prominent plugins like FlaskWTF (for Forms),<br>
>>>> Flask-SQLAlchemy (for databases), Flask-Login (for managing user logins,<br>
>>>> authentications, session management and cookies) and few additional modules<br>
>>>> (like Jsonify). Overall, the session received positive inputs considering<br>
>>>> that it was planned to be a filler (till speakers arrive) lightning talk<br>
>>>> but turned to be a 20 minute talk.<br>
>>>><br>
>>>> This talk was followed by tea and networking. The cool weather outside<br>
>>>> (something Chennai misses too often) and the hot tea and coffee inside<br>
>>>> added energy to the already pumped up pythonistas. Getting to know new<br>
>>>> people, shaking hands, answering queries, taking feedback accompanied with<br>
>>>> good weather - whoa, just awesome! Speakers turned up sometime back and two<br>
>>>> more talks to go as per schedule.<br>
>>>><br>
>>>> Computer Vision with Deep Learning by Manish Shivanandhan<br>
>>>><br>
>>>> Manish started with an introduction of deep learning and how machine<br>
>>>> learning and deep learning differs. Machine learning is more of recognising<br>
>>>> patterns and deep learning is more of learning about patterns. Manish<br>
>>>> covered the different types of learning - supervised, unsupervised and<br>
>>>> reinforcement and gave examples for each of these types; along with<br>
>>>> classification and regression and provided real life examples (housing<br>
>>>> prices, stock prices etc) to compliment the understanding.<br>
>>>><br>
>>>> Coming to neural networks, Manish hinted various algorithms are used<br>
>>>> for deep learning and one of them being Neural networks. He also deciphered<br>
>>>> as to why Neural networks is getting so much traction these days!? - and<br>
>>>> attributed it to the increasing computer processing power and the exploding<br>
>>>> amounts of data.<br>
>>>><br>
>>>> He also highlighted the use cases of Neural networks and its advantages<br>
>>>> and limitations. Prominent examples being:<br>
>>>> Computer vision - pattern recognition in images<br>
>>>> Creative usage - generating text/music/speech<br>
>>>><br>
>>>> One interesting exampling Manish gave is the JK Rowling (Author of<br>
>>>> Harry Potter series) case and how Neural networks helped identify when one<br>
>>>> of her books was written in another pen name (which was not JK Rowling).<br>
>>>> This captivated the audience much more as this is some thing almost all of<br>
>>>> the audience can correlate with. He also stressed the importance of Neural<br>
>>>> networks in the health care domain in finding cure for diseases.<br>
>>>><br>
>>>> He covered how neural networks can be used in Computer vision and deep<br>
>>>> learning. He gave insights into how to take a problem and represent it in<br>
>>>> numbers so that deep learning can be used. He also hinted that if any<br>
>>>> problem can be represented in numbers, deep learning can be used. He demoed<br>
>>>> with an image, flattening it and showing the numbers behind it and<br>
>>>> highlighted that with enough numbers and processing power, patterns can be<br>
>>>> learnt by Neural networks. He complimented that with the Prisma case study<br>
>>>> where researchers took a lot of art manually, scanned it and fed neural<br>
>>>> networks to learn how the great artists like Picaso would have painted the<br>
>>>> picture (the brush strokes, the pressure applied etc). So when an image<br>
>>>> (like selfie) is fed into the Prisma application, the computer generates<br>
>>>> the art form of the image- i.e. how the image would look like if it was a<br>
>>>> painting from Picaso and the likes. This further stressed how deep learning<br>
>>>> can be used and how neural networks can be trained provided sufficient<br>
>>>> clean data is fed into it.<br>
>>>><br>
>>>> Finally, he gave an introduction to TensorFlow and its distinct<br>
>>>> abilities when compared to other frameworks like Theano. Manish finished<br>
>>>> his talk with resources and references for further exploration of Neural<br>
>>>> networks and details about his upcoming webinar. Oh yes, he answered a lot<br>
>>>> of questions on deep learning from an inquisitive audience who were awed by<br>
>>>> the potential of deep learning and bitten by Manish's enthusiasm.<br>
>>>><br>
>>>> Behaviour Driven Development by Naren Ravi<br>
>>>><br>
>>>> Naren provided the background of the talk with a short description of<br>
>>>> what Behaviour Driven Development (BDD) is all about - i.e. testing the<br>
>>>> code with the user in mind and meeting the expectation of the stakeholders<br>
>>>> rather than just testing the code.<br>
>>>><br>
>>>> He started with the waterfall model, the advantages and it's<br>
>>>> limitations. He gave insights into why testing in the later stages of the<br>
>>>> cycle makes life difficult - if bugs encountered and to finally discover<br>
>>>> that the design itself is flawed bringing up frustrations.<br>
>>>><br>
>>>> He then covered how the first optimisation on the waterfall model was<br>
>>>> done with testing the code and informing the development and how further<br>
>>>> optimisation was done to the waterfall model with both testing and<br>
>>>> construction (coding) done parallely. Though these optimisations were done,<br>
>>>> Naren stated that there was an inherent disadvantage that was left with -<br>
>>>> i.e. the design cannot be tested. The solution is to bring the design into<br>
>>>> the development i.e testing, coding and design all tested parallely which<br>
>>>> is the Test Driven Development (TDD).<br>
>>>><br>
>>>> Naren then added that even TDD won't suffice as the requirement<br>
>>>> analysis stage is completely left out. He then questioned the possibility<br>
>>>> of scope (requirements) change and how the SDLC model would adopt it!?<br>
>>>> Bringing the analysis cycle into the above cycle of testing, code and<br>
>>>> design becomes the BDD, he concluded. This gave an overall picture of the<br>
>>>> BDD - testing (test cases) first, construction (coding) and the design and<br>
>>>> finally checking if all of it matches the requirements.<br>
>>>><br>
>>>> He added that in some context, this is how lean startup works. Develop<br>
>>>> a product with a new feature, send it to market, get feedback and then add<br>
>>>> a new feature, send it to market, gauge the reactions and the cycle goes<br>
>>>> on. Overall, it was a well structured talk starting with the traditional<br>
>>>> waterfall model to TDD to BDD and what optimisations were made on the way.<br>
>>>> He answered a few questions later to help bring more clarity into BDD.<br>
>>>><br>
>>>> The meetup ended with Vijay thanking the venue and networking over tea<br>
>>>> sponsors, speakers and the rest who made the meetup a successful event. He<br>
>>>> also asked attendees to register in the mailing list to keep abreast of the<br>
>>>> happenings in the Chennaipy community.<br>
>>>><br>
>>>> Regards<br>
>>>> Azeez<br>
>>>><br>
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>>>><br>
>>>><br>
>>><br>
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