Sep 2017
11 Mon
12 Tue 08:30 AM – 05:20 PM IST
13 Wed 08:30 AM – 05:30 PM IST
14 Thu
15 Fri
16 Sat
17 Sun
Sep 2017
11 Mon
12 Tue 08:30 AM – 05:20 PM IST
13 Wed 08:30 AM – 05:30 PM IST
14 Thu
15 Fri
16 Sat
17 Sun
#About Fragments:
Fragments is a two-day, single track conference on the mobile ecosystem in India. The conference will feature talks – full-length and crisp – panel discussions, and Off-The-Record (OTR) sessions.
Modern Development Practices
Continuous Integration/Continuous Delivery
Design
Localisation and Accessibility
Progressive Web Apps
On the ground case studies
Platform specific talks
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 for 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”.
Proposals will be filtered and shortlisted by an Editorial Panel.
** Make sure to add links to videos / slide decks when submitting proposals. We will not review proposals without detailed outlines or slide decks and preview videos.**
The first filter for every proposal is whether the technology or solution you are referring to is open source or not. If you are referring to a proprietary technology, consider picking up a sponsored session.
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 also helps potential speakers in honing their speaking skills, and rehearsing at least twice - before the main conference - to sharpen the focus of talks.
A speaker is NOT confirmed a slot unless we explicitly mention so in an email or over any other medium of communication.
Selected speakers get a pass to the conference and networking dinner. We do not provide free passes for speakers’ colleagues and spouses.
We also pay an honararium of Rs. 5,000 to each speaker, at the end of their talk.
Fragments 2017 is funded through ticket purchases and sponsorships.
We try to provide full or partial travel grants for at least two international and two domestic speakers.
First preference in awarding grants is given to women speakers, persons of non-binary genders, and speakers from Africa. If you require a travel grant, indicate this in the field where you add your location.
Deadline for submitting proposals: 30 July, 2017
**Conference date: ** 12-13 Sept, 2017
For more information about speaking proposals, contact fragments.editorial@hasgeek.com.
For tickets and sponsorships, contact info@hasgeek.com or call +91-7676332020.
A Naveen Kumar
@4nonymou5
Submitted Aug 18, 2017
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
Conclusion
5 minutes
Basic understanding of AI and their usage
I am a member of the data science team at
Semantics3 - building data-powered software for ecommerce-focused companies. 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.
Sep 2017
11 Mon
12 Tue 08:30 AM – 05:20 PM IST
13 Wed 08:30 AM – 05:30 PM IST
14 Thu
15 Fri
16 Sat
17 Sun
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