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.
#Tracks
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
Format #
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.
Selection process #
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).
Commitment to open source #
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.
Key dates and deadlines #
- 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
##Venue
The Fifth Elephant will be held at the NIMHANS Convention Centre, Dairy Circle, Bangalore.
##Contact
For more information about speaking proposals, tickets and sponsorships, contact info@hasgeek.com or call +91-7676332020.
Hosted by
The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more
AL
Akbar Ladak
@bluplaneter
Bootstrapping inspired by Hacking Human Cognition
Submitted Jun 17, 2016
Section:
Crisp talk
Technical level:
Intermediate
Several applications of Machine Learning are hamstrung by the a vicious cycle.
- An Inaccurate Model provides poor Results which leads to...
- Lack of Investment to procure / train more Data, which further leads to...
- An Inaccurate Model providing poor results.
This vicious cycle can be broken by:
- Either investing in procuring data and “Turking” the data (usually involves poorly paid, unhappy people) or
- Hacking Human Cognition
This talk will focus on hacking the process of human cognition to bootstrap more effectively and increasing accuracy of the model without “Turking”.
Outline #
Several applications of Machine Learning are hamstrung by the a vicious cycle.
- An Inaccurate Model provides poor Results which leads to...
- Lack of investment to procure / train more Data, which further leads to...
- An inaccurate model providing poor results.
This vicious cycle can be broken by:
- Either investing in procuring data and “Turking” the data (usually involves poorly paid, unhappy people) or
- Hacking Human Cognition
This talk will focus on hacking the process of human cognition to bootstrap more effectively and increasing accuracy of the model without “Turking”.
Speaker bio #
Akbar Ladak has conceived, developed & deployed multiple Data Analytics technologies for Text Analytics, Image Analytics & Computer Vision.
He is the inventor & erstwhile Head of Business of Wipro Sight an award winning technology for Computer Vision Computer Vision & Sensor Data analysis that provides enterprises real-time insights on critical aspects of their businesses. Backed by 20 patented & patent pending technologies, Wipro Sight has been deployed for leading Retailers, Medical Devices & Financial Services companies.
He is currently the CEO & Founder of Kaaenaat, a company that focuses on understanding our world better using sensor & image analysis.
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Hosted by
The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more
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