Anthill Inside 2018
On the current state of academic research, practice and development regarding Deep Learning and Artificial Intelligence.
Jul 2018
23 Mon
24 Tue
25 Wed 08:45 AM – 05:25 PM IST
26 Thu
27 Fri
28 Sat
29 Sun
On the current state of academic research, practice and development regarding Deep Learning and Artificial Intelligence.
Jul 2018
23 Mon
24 Tue
25 Wed 08:45 AM – 05:25 PM IST
26 Thu
27 Fri
28 Sat
29 Sun
##About the conference and topics for submitting talks:
In 2016, The Fifth Elephant branched into a separate conference on Deep Learning. The Deep Learning Conference has grown in to a large community under the brand Anthill Inside.
Anthill Inside features talks, panels and Off The Record (OTR) sessions on current research, technologies and developments around Artificial Intelligence (AI) and Deep Learning. Submit proposals for talks and workshops on the following topics:
##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, and a t-shirt.
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.
##Target audience:
We invite beginner and advanced participants from:
to participate in Anthill Inside. At the 2018 edition, tracks will be curated separately for beginner and advanced audiences.
Developer evangelists from organizations which want developers to use their APIs and technologies for deep learning and AI should participate, speak and/or sponsor Anthill Inside.
##Format:
Anthill Inside is a two-day conference with two tracks on each day. Track details will be announced with a draft schedule in February 2018.
We are accepting sessions with the following formats:
##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 honararium 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. Anthill Inside is funded through ticket purchases and sponsorships; travel grant budgets vary.
##Last date for submitting proposals is: 15 April 2018.
You must submit the following details along with your proposal, or within 10 days of submission:
##Contact details:
For information about the conference, sponsorships and tickets contact support@hasgeek.com or call 7676332020. For queries on talk submissions, write to anthillinside.editorial@hasgeek.com
Hosted by
Upendra Singh
@upendrasingh
Submitted Apr 26, 2018
An organization’s data is like a living organism - growing, expanding and evolving over time to form complicated and connected systems. This is similar to biological evolution, where life forms evolved from simple unicellular structures to more and more complex multicellular organisms. And as organizations compile more and more data, it is crucial for them to understand that the value of any data point multiplies only when it can be connected to other data points. So the question they need to ask themselves is ‘Do our current analytics platforms prioritize these data points and its various interrelations?’
To ensure the organization’s needs are met, the data model built for persisting and processing data must support the representation of the relationships both at a logical and persistence level. This is where a Graph based modelling system helps in resolving most of the issues expressed, allowing the query and processing system to leverage data in the best possible way.
So, this talk will describe graph based data modelling and analytics as a means to help organizations figure out the various nuances and hidden elements within their current data models. It will also delve into the various techniques and approaches that will enable them to leverage these data systems. It will cover key questions that organizations typically face: Why should they move to Graph based data modelling? When do they need to start migrating to the Graph paradigm? And How to do this transformation to build analytics from simple aggregations to complex machine learning based analytics?
This talk will describe graph based data modelling and analytics as a means to help organizations figure out the various nuances and hidden elements within their current data models. It will also delve into the various techniques and approaches that will enable them to leverage these data systems. It will cover key questions that organizations typically face: Why should they move to Graph based data modelling? When do they need to start migrating to the Graph paradigm? And How to do this transformation to build analytics from simple aggregations to complex machine learning based analytics?
Upendra Singh is a Lead Big Data Architect at Clustr, working as full stack big data {architect,scientist} and machine learning engineer with a strong base in data engineering and distributed systems development. He comes with over 10 years of experience in building production grade large scale machine learning systems which have been integrated in existing systems. He is adept at building data pipelines for various analytics and data processing use cases. His expertise lies in converting Business Problems into Analytics Solutions, designing the core and assessing the feasibility of Analytics Solutions.
Upendra has a Master’s Degree in Computer Science from Motilal Nehru National Institute Of Technology and a Bachelor’s Degree from Punjab University. Prior to Clustr, he has worked with technology leaders such as Robert Bosch, Dell R&D India and Dell EMC.
Jul 2018
23 Mon
24 Tue
25 Wed 08:45 AM – 05:25 PM IST
26 Thu
27 Fri
28 Sat
29 Sun
Hosted by
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