The Fifth Elephant is India’s most renowned data science conference. It is a space for discussing some of the most cutting edge developments in the fields of machine learning, data science and technology that powers data collection and analysis.
Machine Learning, Distributed and Parallel Computing, and High-performance Computing continue to be the themes for this year’s edition of Fifth Elephant.
We are now accepting submissions for our next edition which will take place in Bangalore 28-29 July 2016.
We are looking for application level and tool-centric talks and tutorials on the following topics:
- Deep Learning
- Text Mining
- Computer Vision
- Social Network Analysis
- Large-scale Machine Learning (ML)
- Internet of Things (IoT)
- Computational Biology
- ML in healthcare
- ML in education
- ML in energy and ecology
- ML in agriculrure
- Analytics for emerging markets
- ML in e-governance
- ML in smart cities
- ML in defense
The deadline for submitting proposals is 30th April 2016
This year’s edition spans two days of hands-on workshops and conference. We are inviting proposals for:
- Full-length 40 minute talks.
- Crisp 15-minute talks.
- Sponsored sessions, 15 minute duration (limited slots available; subject to editorial scrutiny and approval).
- Hands-on Workshop sessions, 3 and 6 hour duration.
Proposals will be filtered and shortlisted by an Editorial Panel. We urge you to add links to videos / slide decks when submitting proposals. This will help us understand your past speaking experience. Blurbs or blog posts covering the relevance of a particular problem statement and how it is tackled will help the Editorial Panel better judge your proposals.
We expect you to submit an outline of your proposed talk – either in the form of a mind map or a text document or draft slides within two weeks of submitting your proposal.
We will notify you about the status of your proposal within three weeks of submission.
Selected speakers must participate in one-two rounds of rehearsals before the conference. This is mandatory and helps you to prepare well for the conference.
There is only one speaker per session. Entry is free for selected speakers. As our budget is limited, we will prefer speakers from locations closer home, but will do our best to cover for anyone exceptional. HasGeek will provide a grant to cover part of your travel and accommodation in Bangalore. Grants are limited and made available to speakers delivering full sessions (40 minutes or longer).
HasGeek believes in open source as the binding force of our community. If you are describing a codebase for developers to work with, we’d like it to be available under a permissive open source licence. If your software is commercially licensed or available under a combination of commercial and restrictive open source licences (such as the various forms of the GPL), please consider picking up a sponsorship. We recognise that there are valid reasons for commercial licensing, but ask that you support us in return for giving you an audience. Your session will be marked on the schedule as a sponsored session.
- Revised paper submission deadline: 17 June 2016
- Confirmed talks announcement (in batches): 13 June 2016
- Schedule announcement: 30 June 2016
- Conference dates: 28-29 July 2016
The Fifth Elephant will be held at the NIMHANS Convention Centre, Dairy Circle, Bangalore.
For more information about speaking proposals, tickets and sponsorships, contact email@example.com or call +91-7676332020.
Machine Learning - Democratized
Machine Learning is no more a science for data scientists and data engineers, the cloud based machine learning services have democratized the entire process of Machine learning, right from the Data science to the data engineers to the data visualization. You no longer need to be an expert in either to take a taste of Machine learning or see how it works. The cloud based ML options even allow you to go a step ahead and try with custom Python and R code, we’ll write a little as well ourselves.
- Introduction to Machine learning basics
a. How does Machine learning works
b. What kind of tools do Machine learning pros use to do ML and Why is it considered a complex scienece.
- Introduction to Cloud based Machine learning options
a. Introduction to various cloud implementations of Machine Learning platforms, and Why do you need the cloud based Machine learning platforms.
b. Myth or fact - are the Cloud based Machine learning platforms tying you down with themselves or you can still do the open source programming and yet use them.
c. See how a newbie of Machine Learning can yet try to make a Model and re-use some established Machine learning algorithms like Recommendation engine.
- Write a Machine learning implementation and use it in your application.
a. Author a Machine learning model in one of the cloud implementation, and make it usable to developers there and then.
- May be bring in some python or R code to the ML implementation
a. Write your custom Python or R code and use Jupyter notebooks in the cloud based model as well.
Anyone who wants to learn Machine learning
I am a Sr. Technology Evangelist (Open Source solutions) with Microsoft. I have a decade worth of experience in both Microsoft technologies as well as with open source technologies. I have architected highly scalable and reliable solutions using Open source technologies.
I regularly speak at 3rd party conferences, I love to work with technologies that make developers lives easy, every now and then a new product comes out that makes the processes more easier, my job is to bring that knowledge to devs and make our lives simpler, because everyone has other things to do.