The Fifth Elephant round the year submissions for 2019
Submit a talk on data, data science, analytics, business intelligence, data engineering and ML engineering
Make a submission
Accepting submissions till 31 Dec 2020, 11:59 PM
Submit a talk on data, data science, analytics, business intelligence, data engineering and ML engineering
Accepting submissions till 31 Dec 2020, 11:59 PM
If you missed the deadline for submitting your talk for The Fifth Elephant 2019 -- to be held in Bangalore on 25 and 26 July -- you can propose a talk here.
We are accepting talks on:
##Perks for submitting proposals:
Submitting a proposal, especially with our process, is hard work. We appreciate your effort.
We offer one conference ticket at discounted price to each proposer.
We only accept one speaker per talk. This is non-negotiable. Workshops may have more than one instructor.
In case of proposals where more than one person has been mentioned as collaborator, we offer the discounted ticket and t-shirt only to the person with who the editorial team corresponded directly during the evaluation process.
##Selection criteria:
The first filter for a proposal is whether the technology or solution you are referring to is open source or not. The following criteria apply for closed source talks:
The criteria for selecting proposals, in the order of importance, are:
No one submits the perfect proposal in the first instance. We therefore encourage you to:
Our editorial team helps potential speakers in honing their speaking skills, fine tuning and rehearsing content at least twice - before the main conference - and sharpening the focus of talks.
##How to submit a proposal (and increase your chances of getting selected):
The following guidelines will help you in submitting a proposal:
To summarize, we do not accept talks that gloss over details or try to deliver high-level knowledge without covering depth. Talks have to be backed with real insights and experiences for the content to be useful to participants.
##Passes and honorarium for speakers:
We pay an honorarium of Rs. 3,000 to each speaker and workshop instructor at the end of their talk/workshop. Confirmed speakers and instructors also get a pass to the conference and networking dinner. We do not provide free passes for speakers’ colleagues and spouses.
##Travel grants for outstation speakers:
Travel grants are available for international and domestic speakers. We evaluate each case on its merits, giving preference to women, people of non-binary gender, and Africans. If you require a grant, request it when you submit your proposal in the field where you add your location. The Fifth Elephant is funded through ticket purchases and sponsorships; travel grant budgets vary.
You must submit the following details along with your proposal, or within 10 days of submission:
Hosted by
A Naveen Kumar
The ability to train the task specific deep learning models is very easy these
days, with the wide range of available libraries and documentation around it. But,
the difficulty lies in bringing it to production ready mode. Especially, if the
application concentrates on Mobile platform. Though there are existing wrappers of certain libraries to make them work, but,
as of now, they are slow and use up almost the entire memory space of the
phone.
In this talk, I would like to explain, what can be done to make things faster and
how to make models with reduced size. The aim of this talk is to provide insights
on what would be the difficulties which lie ahead and how to build your own
libraries in both iOS and Android.
What is Deep Learning ?
5 mins, introduction and explanation
What are the difficulties faced to push them into mobile production ?
10 minutes
How to solve it in IOS ?
5 minutes
How to solve it in Android ?
5-10 minutes
How to solve it on other edge devices ?
5-10 minutes
Conclusion
5 minutes
Generic Idea of creating deep learning models and there deployement.
I am a member of the data science team at Here Maps - Automating Maps. Over the years, I have had the chance to work on various aspects of Deep Learning, one such scenario was running the models on mobile. We made an app named Flo, which got featured by Apple on their twitter page for using AI and their framework to make it run faster. Currently, I am working on making perception modules run on the edge devices.
https://docs.google.com/presentation/d/135rZx7wDIozqBsKQRxl0p7mOyWKwXoKD14vlqRJPlVY/edit?usp=sharing
Accepting submissions till 31 Dec 2020, 11:59 PM
Hosted by
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