Anthill Inside 2019

A conference on AI and Deep Learning

Make a submission

Accepting submissions till 01 Nov 2019, 04:20 PM

Taj M G Road, Bangalore, Bangalore

##About the 2019 edition:

The schedule for the 2019 edition is published here: https://hasgeek.com/anthillinside/2019/schedule

The conference has three tracks:

  1. Talks in the main conference hall track
  2. Poster sessions featuring novel ideas and projects in the poster session track
  3. Birds of Feather (BOF) sessions for practitioners who want to use the Anthill Inside forum to discuss:
  • Myths and realities of labelling datasets for Deep Learning.
  • Practical experience with using Knowledge Graphs for different use cases.
  • Interpretability and its application in different contexts; challenges with GDPR and intepreting datasets.
  • Pros and cons of using custom and open source tooling for AI/DL/ML.

#Who should attend Anthill Inside:

Anthill Inside is a platform for:

  1. Data scientists
  2. AI, DL and ML engineers
  3. Cloud providers
  4. Companies which make tooling for AI, ML and Deep Learning
  5. Companies working with NLP and Computer Vision who want to share their work and learnings with the community

For inquiries about tickets and sponsorships, call Anthill Inside on 7676332020 or write to sales@hasgeek.com


#Sponsors:

Sponsorship slots for Anthill Inside 2019 are open. Click here to view the sponsorship deck.


Anthill Inside 2019 sponsors: #


#Bronze Sponsor

iMerit Impetus

#Community Sponsor

GO-JEK iPropal
LightSpeed Semantics3
Google Tact.AI
Amex

Hosted by

Anthill Inside is a forum for conversations about Artificial Intelligence and Deep Learning, including: Tools Techniques Approaches for integrating AI and Deep Learning in products and businesses. Engineering for AI. more

Khaleeque Ansari

@khaleeque-ansari

Dataset Denoising : Improving Accuracy of NLP Classifier

Submitted Apr 30, 2019

Reliable evaluation for the performance of classifiers depends on the quality of the data sets on which they are tested. During the collecting and recording of a data set, however, some noise may be introduced into the data, especially in various real-world environments, which can degrade the quality of the data set.
In this talk we will discuss how we at MakeMyTrip are continuously improving performance of our deep learning based NLP classifier by correcting mislabeled data & reducing noise from our huge dataset.

Outline #

  • Introduction of the problem statement.
  • Identifying mislabeled data.
  • Algorithm to correct mislabeled data.
  • Results/ Performance Improvement.

Speaker bio #

I am Khaleeque Ansari, Lead Data Scientist at MakeMyTrip, where we’re developing Myra, MakeMyTrip’s task bot for assisting millions of our customers with post sale issues such as cancelling & modifying bookings, enquiring about flight status, baggage limits, refund status etc.
I have done my Bachelors in Computer Science from IIT Delhi. My principal research interests lie in NLP & have more than 5 years of experience building NLP models for the industry.

Slides #

https://docs.google.com/presentation/d/1WswqW_QWwM2Qrj9jl-HevsLiuRvsPnJ6DiTiUtCLNsM/edit#slide=id.p1

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Make a submission

Accepting submissions till 01 Nov 2019, 04:20 PM

Taj M G Road, Bangalore, Bangalore

Hosted by

Anthill Inside is a forum for conversations about Artificial Intelligence and Deep Learning, including: Tools Techniques Approaches for integrating AI and Deep Learning in products and businesses. Engineering for AI. more