Jul 2016
27 Mon
28 Tue
29 Wed
30 Thu
1 Fri 08:45 AM – 06:15 PM IST
2 Sat 08:15 AM – 02:15 PM IST
3 Sun
Deep Learning is a new area of research that is getting us closer in achieving one of the primary objectives of Machine Learning – Artificial Intelligence.
It is used widely in the fields of Image Recognition, Natural Language Processing (NLP) and Video Classification.
Deep Learning Conf is a single day conference followed by workshops on the second day. The conference will have full, crisp and lightning talks from morning to evening. The workshops on the next day will introduce participants to neural networks followed by two tracks of three-hour workshops on NLP and Computer Vision / AI. Participants can join either one of the two workshop tracks.
##Tracks
We are looking for talks and workshops from academics and practitioners of Deep Learning on the following topics:
We are inviting proposals for:
Proposals will be filtered and shortlisted by an Editorial Panel. Along with your proposal, you must share the following details:
If your proposal involves speaking about a library / tool / software that you intend to open source in future, the proposal will be considered only when the library / tool / software in question is made open source.
We will notify you about the status of your proposal within two-three weeks of submission.
Selected speakers have to participate in one-two rounds of rehearsals before the conference. This is mandatory and helps you prepare for speaking at 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).
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.
##Venue
CMR Institute of Technology, Bangalore
##Contact
For more information about speaking proposals, tickets and sponsorships, contact info@hasgeek.com or call +91-7676332020.
Hosted by
Sunita John
@sunjoh
Submitted May 26, 2016
Deep learning is now within reach for anyone to use!
We will explore real-world applications of deep learning by showing demos of transfer learning and real-time object recognition. Deep learning models can be difficult to train, evaluate and compare. In this session we will explore how MATLAB addresses the most common challenges such as handling large sets of images and retraining existing network architectures.
We’ll highlight the computer vision workflow using Deep Learning with MATLAB including:
1.Accessing and managing large sets of images
2.Leveraging the use of pre-trained networks for transfer learning
3.Using standard computer vision techniques to augment the use of deep learning
4.Speeding up the training process using GPUs
Amit Doshi, MathWorks India
Amit Doshi is an application engineer at MathWorks in the area of technical computing. He focuses on data acquisition, data presentation, statistical analysis, and parallel computing. Amit has over 9 years of experience in experimental test setup development, testing and validation, workflow automation, and system simulations. He previously worked at Suzlon Energy Limited in Pune and Germany, Texas Instruments in Germany, and IIT Bombay. Amit holds a bachelor’s degree in mechanical engineering and a master’s degree in mechatronics
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