Anthill Inside 2019

A conference on AI and Deep Learning

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Submissions are closed for this project

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

lavanya TS

@lavanyats

Building Products with ML: A Workshop for Product & Engg Managers

Submitted Aug 20, 2019

Machine learning (ML) has seen substantial adoption, and a large number of data
science teams are being created. Taking on ML projects requires product managers
and engineers to learn an ML approach to problem solving, to be able to effectively
work with data scientists and data engineers. There exists a huge gap in understanding
- both cultural & technical - in most organizations since product owners and the
engineering teams have not worked with ML before. The ML approach is sufficiently
different from a usual software engineering approach that it needs deeper
understanding and adoption

The aim of this workshop is to acquaint product managers and engineering managers
with ML ways, to effectively lead ML teams producing outcomes of value.

Outline

The workshop starts with an introduction to ML to get an intuitive understanding of ML algorithms work,
and covers the typical project lifecycle and roles and responsibilities. It also covers
common mistakes while executing ML products followed by best practices & design
patterns from an ML software perspective. Finally, there is a brief session on ML data
governance challenges. Multiple case studies are discussed to illustrate these concepts,
along with interactive sessions to practice applying the content to custom usecases.

Requirements

Should have 5+ years experience in the Industry. Preferably people who
have worked as a Product Manager / Engineering Manager before.

Speaker bio

Lavanya Sita Tekumalla is a Machine Learning Scientist and the founder of AiFonic Labs. She holds a PhD in Machine Learning (Bayesian Models) from the Indian Institute of Science and a Masters in Computer Graphics from the Uninversity of Utah. She has been in the Industry for over 9 years in various roles (Ex-Amazon-twice, InMobi, Myntra, Kenome). She has also owned product and helped with ML at Kenome, a deep-tech startup until recently.

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Willem Pienaar

Feast: Feature Store for Machine Learning

Features are key to driving impact with AI at all scales, allowing organizations to dramatically accelerate innovation and time to market. Willem Pienaar explain how GOJEK, Indonesia’s first billion-dollar startup, unlocked insights in AI by building a feature store called Feast, and some of the lessons they learned along the way. more

20 Aug 2019