Deep Learning Conf 2016

A conference on deep learning.

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.

Format

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:

  • Applications of Deep Learning in software.
  • Applications of Deep Learning in hardware.
  • Conceptual talks and cutting edge research on Deep Learning.
  • Building businesses with Deep Learning at the core.

We are inviting proposals for:

  • Full-length 40 minute talks.
  • Crisp 15-minute talks.
  • Lightning talks of 5 mins duration.

Selection process

Proposals will be filtered and shortlisted by an Editorial Panel. Along with your proposal, you must share the following details:

  • Links to videos / slide decks when submitting proposals. This will help us understand your past speaking experience.
  • Blog posts you may have written related to your proposal.
  • Outline of your proposed talk – either in the form of a mind map or a text document or draft slides.

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).

Commitment to open source

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.

Key dates and deadlines

  • Proposal submission deadline: 31 May 2016
  • Schedule announcement: 15 June 2016
  • Conference dates: 1 July 2016

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

The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more
Nischal HP

Nischal HP

@nischalhp

Introduction to Deep Learning for Natural Language Processing

Submitted Apr 29, 2016

This workshop will provide an introduction to deep learning for natural language processing (NLP). It will cover some of the common deep learning architectures, describe advantages and concerns, and provide hands-on experience.

Outline

We would cover the following:

  1. What is deep learning?
  2. Motivation: Some use cases where it has produced state-of-art results
  3. Basic building blocks of Neural networks (Neuron, activation function, back propagation algorithm, gradient descent algorithm)
  4. Supervised learning (multi-layer perceptron, recurrent neural network)
  5. Introduction to word2vec
  6. Introduction to Recurrent Neural Networks
  7. Text classification using RNN
  8. Impact of GPUs (Some practical thoughts on hardware and software)

Broadly, there will be three hands-on modules

  1. A simple multi-layer perceptron - to understand basics of neural networks (everything will be coded from scratch)
  2. Vectorization hands-on using Word2vec
  3. A text classification problem and a text generation problem: This will be solved using Recurrent Neural Networks.

Requirements

Laptop with python packages installed.

  • Anaconda for Python 2
  • Keras - pip install keras
  • Lots of enthusiasm

Speaker bio

Nischal is co founder and Data Engineer at Unnati Data Labs who enables the Data Scientists to work at peace. He makes sure that they get the data they need and in the way they need it. Previously he has built, from scratch, various systems for E-commerce like catalog management, recommendation engines and other systems that amass a lot of data, during his tenure at Redmart.

At SAP Labs, Nischal has built various data crawlers, intention mining systems and laid down initial work on an end to end Text Mining/Analysis Pipeline. The majority of his work, however, was centered around building a system that gamified technical indicators in a product for the Fintech domain.

He has conducted workshops in the field of Deep learning across the world. He is a strong believer of open source and loves to architect big, fast and reliable systems. In his free time, he enjoys psychedelic trance and travelling to remote places.

Raghotham is a Data Scientist who can work across the complete stack. Previously, at Touchpoints Inc., He single handedly built a data analytics platform for a fitness wearable company. With Redmart, he worked on the CRM system and has built a sentinment analyzer for Redmart’s Social Media. Prior to Redmart and Touchpoints, Raghotham worked at SAP Labs where he was a core part of what is currently SAP’s framework for building web and mobile products. He was a part of multiple SAP wide events helping to spread the knowledge both internally and to customers.

Having found deep love for data science, neural networks and the passion for teaching, Raghotham has conducted workshops across the world. Apart from getting his hands dirty with data, he loves travelling, Pink Floyd and masala dosas.

Links

Slides

https://speakerdeck.com/unnati_xyz/introduction-to-deep-learning-for-nlp

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Hosted by

The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more