Anand is a co-founder of Gramener, a data science company. He leads a team of data enthusiasts with skills in analysis, design, programming and statistics. He studied at IIT Madras, IIM Bangalore and LBS, and worked at IBM, Infosys, Lehman Brothers and BCG. He and his team explore insights from data and communicate these as visual stories. These visual analyses and dashboards are built on the Gramener Visualisation Server.
This workshop focuses on the use of Python, NumPy, pandas & scikit-learn for (financial) time series analysis. It starts with the basics, addresses some advanced topics in the context of performance and also illustrates the application of machine learning algorithms to the prediction of (financial) time series.
Founder & Managing Partner, The Python Quants GmbH
Dr. Yves J. Hilpisch is founder and managing partner of The Python Quants (http://tpq.io), a group focusing on the use of open source technologies for financial data science, algorithmic trading and computational finance. He is the author of the books:
- Python for Finance (O'Reilly, 2014),
- Derivatives Analytics with Python (Wiley, 2015) and
- Listed Volatility and Variance Derivatives (Wiley, 2017).
Yves lectures on computational finance at the CQF Program (http://cqf.com), on data science at htw saar University of Applied Sciences (http://htwsaar.de) and is the director of the first online training program leading to a Python for Algorithmic Trading University Certificate (awarded by htw saar).
Yves has written the financial analytics library DX Analytics (http://dx-analytics.com) and organizes meetups and conferences about Python for quantitative finance in Frankfurt, London and New York. He has given keynote speeches at technology conferences in the United States, Europe and Asia.
Director, Python Software Foundation
Freedom of The Press Foundation
Kushal is working with Fedora Project over last 10 years in various capacities and currently working as Fedora Cloud Engineeer in Red Hat. He is also a core developer of CPython, and director at Python Software Foundation. In 2004 he founded dgplug and still helps there as a co-ordinator.
Programming is fun. It is even more so when we program just of the fun of it, without any practical value. How about building a game, solving a puzzle, writing a compiler, making a fractal or even writing a programming language?
Software Consultant & Trainer, Pipal Academy
Anand has been crafting beautiful software since a decade and half. He’s now building a data science platform, rorodata, which he recently co-founded. He regularly conducts advanced programming courses through Pipal Academy. He is co-author of web.py, a micro web framework in Python. He has worked at Strand Life Sciences and Internet Archive.
Contributing to an Open Source project not only helps you to get a better job, also helps to learn lots of skills, technology, communication and knowing people across the globe. But start contributing to Open Source appears to be hard as it requires an effort to make a contribution.
Everyone possess some skills but we need some guidance to getting started as it is not so hard. It just requires being getting started, always stay contributing, once you feel mature, you need to stick to any community. Patience and Time plays an important role in shaping your future in this world.
I will be sharing my journey to opensource how I had started as a open source translator to open source developer for RDO community.
The talk will highlight:
* What is contribution and why should I contribute?
* How have I started contributing while I was in college.
* Follow the master to become the master.
* Frustration, burnout while contributing to Open Source and how to overcome it.
* Knowing the community and stay motivated.
* How I got involved with RDO community.
* Reached a goal and what next?
Computational science has changed the way we do science and engineering. However, most computational scientists are not trained to be effective computer programmers. They are instead expected to just 'pick it up'. As most practitioners will attest, this is not easy and leads to a host of problems.
I am an aerospace engineer by training and have been programming with Python and other languages for many years and have made many mistakes. Fortunately, I have learned some lessons while making these mistakes. In this talk I'll first talk very briefly about the various things I've had to build as a non-CSE engineer over the last two decades and then go over several lessons that I have found useful when I write code today. Many of these lessons are fairly well known. I plan to put these ideas in the context of a computational scientist and the challenges they face guided by my own experiences. My hope is that these general rules will help others be better programmers.
Faculty Member, Department of Aerospace Engineering, IIT Bombay
Prabhu Ramachandran has been a faculty member at the department of Aerospace engineering, IIT Bombay, since 2005. His research interests are primarily in particle methods for fluid flow simulation and applied scientific computing.
He has been active in the FOSS/Python community for close to two decades. Along with his students, he has been building an open source framework for particle simulations called PySPH. He is the creator, author, and lead developer of the award winning Mayavi Python package. He is an active member of the SciPy community. He has been a nominated fellow of the Python Software Foundation since 2010. He was awarded the Kenneth Gonsalves award by the Python Software Society of India and PSF in 2014. He is the PI of the FOSSEE project. He was the managing director of Enthought India between 2011 and 2013 and currently serves as a director of the company.
The objective of the workshop is to understand how various sensors and actuators are accessed and controlled from a Linux based embedded system.
This will be a starting point for people who want to build connected and IoT enabled embedded systems using Linux.
Embedded Systems are no longer restricted to firmware developers. With Linux being used in many embedded systems, Java and Python developers can also build useful products using these systems.
This workshop will help application developers learn how to interface with the sensors and actuators using interfaces like Serial, I2C, GPIO, PWM and ADC, from a high level language like Python.
Embedded Software Developer, Zilogic Systems
Vijay is an embedded software developer and trainer by profession. He conducts training in various topics related to Embedded Systems, Linux and Python. At his current company, Zilogic Systems, they have helped several companies, in the Chennai region, migrate their firmware based embedded products to Linux.
He also co-ordinates the activities of Chennaipy. In the past 5 years, he has done over 50 talks at Chennaipy. His work at Chennaipy was recognized by the PSSI, with the Kenneth Gonsalves Award, for the year 2015.
1. Understand how chatbots work.
2. Learn to build a simple bot.
Founder, iMorph Inc.
CTO, Future Focus/Focus America
Dorai Thodla has over 40 years experience in Software Industry and he has founded 4 product startups - 2 in India and 2 in USA. Currently he is working in below roles:
- CTO of Future Focus/Focus America
- Innovation Mentor at KCG College of Technology
- Innovation Mentor at Hindustan University
- Founder of product company iMorph Innovations
- Founder of Technology Strategies LLC, CA, USA
- Helps build Software Skills, Product Skills and Startup Skills
- Teacher, Mentor, Community Builder
Brief Outline of the Talk
1. What is web scraping ?
2. Why should you scrape ?
3. Things that might come handy
4. How it’s done
5. Comparing Parsers
6. Preserving the data
7. Code Examples
8. What to use when to use
9. Scraping Hacks
10. Ethics of Scraping
11. Q/A and General Discussion
Hello world !
I am a web developer and an open source enthusiast, I am also a Python lover and use it to automate everything I can. Being an open source developer I am an active member of the various local user group that supports and promote open source. Recently I spoke at PyDelhi Conf 2017 about automation using python and my talk was titled as 'A lazy programmer’s guide to automation'.
Backend Engineer, Mad Street Den
An optimist by nature, Naren shows up late to meetings at MadStreetDen. In his 4 years of industry experience he’s worn plenty of hats- like the one of a Trainer, Embedded Engineer and Backend/Product Engineer and sometimes even helmets- when he’s out cycling. He is currently on a mission to help startups to design and write usable software even before making it reusable. When he’s not stirring up code, you can find him whipping up a delicious gluten-free treat or travelling/cycling. He likes being asked about his endless love for Python through the handle @DudeWhoCode
Ever wanted a personal assistant like Jarvis for yourself? Fear not. Stephanie addresses the problem by providing an open-source platform built specifically for voice-controlled applications as well as to automate daily tasks and hence imitating much of a virtual/personal assistant’s job.
The objective of the talk will be to give first hand experience of teaching people on how to create their own simple AI with Stephanie with just a couple of clicks after downloading the files and then providing a tutorial on how to create their own modules so that they could harness the true ability of virtual assistant.
Hey there! My name is Ujjwal Gupta, creator of Stephanie. I am an 18 year old self taught programmer and am not been going to college as I strongly believe the internet and Open Source Community has more than enough resources available for any programming enthusiast to master it’s craft.
I have prior knowledge about web development as well as software development and been working as a freelancer in my spare time. I really love to follow football and do side/personal projects for fun as a hobby. I have been recently working on a NLP solution through sounder by making it more efficient and less computationally expensive to use.
Artificial Neural Networks (ANN henceforth) are being used increasingly ever in recent years, and some consider it as a master key for almost all machine learning problems. There are many toolkits and libraries (tools henceforth) available, but I myself have never been comfortable with such tools until I understand (at least partially) what’s going on under the hood. I’m in no way saying that these tools are poorly documented or have a difficult learning curve, it’s just the way I tend to learn. Assuming that I am not alone in this regard, I would like to help others in their quest to understand and master ANN by giving my bit.View presentation