Anthill Inside 2017
On theory and concepts in Machine Learning, Deep Learning and Artificial Intelligence. Formerly Deep Learning Conf.
Jul 2017
24 Mon
25 Tue
26 Wed
27 Thu
28 Fri
29 Sat 09:00 AM – 05:40 PM IST
30 Sun
On theory and concepts in Machine Learning, Deep Learning and Artificial Intelligence. Formerly Deep Learning Conf.
Jul 2017
24 Mon
25 Tue
26 Wed
27 Thu
28 Fri
29 Sat 09:00 AM – 05:40 PM IST
30 Sun
##About AnthillInside:
In 2016, The Fifth Elephant branched into a separate conference on Deep Learning. Anthill Inside is the new avataar of the Deep Learning conference.
Anthill Inside attempts to bridge the gap bringing theoretical advances closer to functioning reality.
Proposals are invited for full length talks, crisp talks and poster/demo sessions in the area of ML+DL. The talks need to focus on the techniques used, and may be presented independent of the domain wherein they are applied.
We also invite talks on novel applications of ML+DL, and methods of realising the same in hardware/software.
Case studies of how DL and ML have been applied in different domains will continue to be discussed at The Fifth Elephant.
https://anthillinside.in/2017/
##Format:
Anthill Inside is a two-track conference:
We are inviting proposals for:
You must submit the following details along with your proposal, or within 10 days of submission:
##Selection Process:
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 to start evaluating your proposal.
You can check back on this page for the status of your proposal. We will notify you if we either move your proposal to the next round or if we reject it. Selected speakers must participate in one or two rounds of rehearsals before the conference. This is mandatory and helps you to prepare well for the conference.
A speaker is NOT confirmed a slot unless we explicitly mention so in an email or over any other medium of communication.
There is only one speaker per session. Entry is free for selected speakers.
We might contact you to ask if you’d like to repost your content on the official conference blog.
##Travel Grants:
Partial or full grants, covering travel and accomodation are made available to speakers delivering full sessions (40 minutes) and workshops. Grants are limited, and are given in the order of preference to students, women, persons of non-binary genders, and speakers from Asia and Africa.
##Commitment to Open Source:
We believe 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), you should consider picking up a sponsorship. We recognise that there are valid reasons for commercial licensing, but ask that you support the conference in return for giving you an audience. Your session will be marked on the schedule as a “sponsored session”.
##Important Dates:
##Contact:
For more information about speaking proposals, tickets and sponsorships, contact info@hasgeek.com or call +91-7676332020.
Please note, we will not evaluate proposals that do not have a slide deck and a video in them.
Hosted by
Satwik Kansal
Most of the people would have heard of Deepmind’s AI getiing really good at playing Atari games.
In this talk, we’ll focus on developing a similar but simpler agent that uses Reinforcement Learning algorithms to learn to play such games on its own. The session will progress from a gentle introduction to the Reinforcement Learning (RL) concepts, steps involved gradually in identifying and modelling a RL problem. The complexity of RL algorithm described in the session will escalate from simple table based Q-learning algorithm, to simple neural network based RL and then finally to highly efficient Deep Q networks.
For demonstration, we’ll be using Open AI gym to simulate the game environment and ipython notebooks to document and display the code.
After this beginner-friendly session, the audience will be able to understand how Reinforcement Learning algorithms work at a broader level and develop their own game agent.
First 10 minutes:
Initially, the audience is introduced to Reinforcement Learning (RL) and some of the standard terms and concepts like Agents, state, policy, etc.
Next 10 minutes:
We will walk through the implementation of Q-Learning (an RL technique) to develop an Agent that learns to adapt to the game environment provided by Open AI and gets smarter with every move by learning ‘policies’ and ‘strategies.’
Next 15 minutes:
We’ll talk through the design of simple single-layered Neural network algorithm and finally, go through the implementation of Deep-Q network for the same game environment.
Final 10 minutes:
The session will conclude with some general discussion regarding scope and limitations of these Reinforcement learning techniques and the current state of the Reinforcement Learning in terms of applications and availability of open source libraries.
Basic programming knowledge, rough knowledge of how Neural Networks work will also be helpful.
A Junior pursuing Bachelors in Software Engineering. Also, a Freelance Software Developer having experience in Machine Learning and Web Development.
I actively contribute to some Open Source projects. In my leisure time, I like to learn about new technologies like AI, Decentralized Applications, AR/VR, explore the trends, and work on ideas involving these technologies.
I usually conduct sessions on Python and Android development as a part of DTU: Open Source Software Development group. I’ve gained all the knowledge this talk requires from some quality MOOCs, popular articles on the web, and Udacity’s Machine Learning Nanodegree that I was enrolled in.
I regularly participate in Hackathons and community meetups and have won several hackathons over the past year. And lastly, I like all things Python!
https://docs.google.com/presentation/d/1vBW8-ML5PMoQIE5oF1zhYUTqSQIL75ubMRG-LHtQuvw/edit?usp=sharing
Jul 2017
24 Mon
25 Tue
26 Wed
27 Thu
28 Fri
29 Sat 09:00 AM – 05:40 PM IST
30 Sun
Hosted by
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