Jul 2018
23 Mon
24 Tue
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26 Thu 07:45 AM – 06:15 PM IST
27 Fri 07:45 AM – 05:35 PM IST
28 Sat
29 Sun
##About the conference and topics for submitting talks:
The Fifth Elephant is rated as India’s best data conference. It is a conference for practitioners, by practitioners. In 2018, The Fifth Elephant will complete its seventh edition.
The Fifth Elephant is an evolving community of stakeholders invested in data in India. Our goal is to strengthen and grow this community by presenting talks, panels and Off The Record (OTR) sessions that present real insights about:
**
##Target audience:
You should attend and speak at The Fifth Elephant if your work involves:
##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.
##Format:
The Fifth Elephant 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 honorarium 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. The Fifth Elephant is funded through ticket purchases and sponsorships; travel grant budgets vary.
##Last date for submitting proposals is: 31 March 2018.
You must submit the following details along with your proposal, or within 10 days of submission:
##Contact details:
For more information about the conference, sponsorships, or any other information contact support@hasgeek.com or call 7676332020.
Hosted by
Nishant Nikhil
@nishnik
Submitted Feb 1, 2018
King - Man + Woman = Queen
The most famous example of word vectors paint an optimistic picture where computers can represent word into vectors which can be used to infer similarity. But can we extend it to sentences or to documents? How did word vectors come into existence? What are its utilities?
Though most of the people use Mikolov et al’s Word2Vec as a blackbox and train by:
import gensim
sentences = [[‘content’, ‘of’, ‘first’, ‘sentence’], [‘content’, ‘of’, ‘second’, ‘sentence’], ... , [‘content’, ‘of’, ‘nth’, ‘sentence’]]
model = gensim.models.Word2Vec(sentences)
And never know what is cooking inside the hood. This talk would cover a very basic implementation of Word2Vec, a small tutorial of how to use Gensim to train your own word vectors. Building on this we would build vector representation of sentences. We would meanwhile learn about the novelty of classical and deep learning techniques.
After learning all this we would explore the application of Word Movers’ Distance for Information retrieval.
Though these terms sound new, but this talk would build from the very basics(arrays as vectors) and myself being a programmer, along with Deep Learning enthusiast, would focus more on a progammer’s perspective.
Coverage of the workshop:
Introduction to NLP -> 10 minutes
Tokenization, Stemming and Lemmatization -> 25 minutes (10-15 minutes of Hands on session)
Brief intro of POS and NER -> 10 minutes
Word Embeddings (Theory and Motivation) -> 10 minutes
Word Embeddings (Hands on)
Basic Implementation -> 15 minutes
Gensim based Implementation (Meanwhile explaining the possible use cases) -> 15 minutes
Introduction to Deep Learning and exciting stuff for future (10 minutes)
Small intoduction to PyTorch/Keras (Hands on) (10 minutes)
Basics about one-hot encoding, and explaining the hello world of neural networks (10 minutes)
Learning word embeddings and a glimpse of Transfer Learning (Hands on) (20 minutes)
Introduction to Sentence embedding (10 minutes)
Word Movers’ Distance for Information Retrieval (15 minutes)
Remaining as buffer time
The speaker is a fourth year undergraduate student at IIT Kharagpur. A robotics and deep learning enthusiast, he spends his time writing blogs about Artificial Intelligence where he was a top writer till June 2017 or teaching humanoid robots to walk and kick at the KRSSG Lab otherwise maintaining the college wiki.
He was a GSoC mentor for SymEngine/SymPy in 2017 where he was a GSoC student in 2016. Furthermore, he has worked on Cross Lingual Word embeddings at UFAL Prague, generating pattern of birds’ songs at ETH Zurich and hierarchical embeddings at Stony Brooks NYC.
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