##About the 2019 edition:
The schedule for the 2019 edition is published here: https://hasgeek.com/anthillinside/2019/schedule
The conference has three tracks:
- Talks in the main conference hall track
- Poster sessions featuring novel ideas and projects in the poster session track
- 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:
- Data scientists
- AI, DL and ML engineers
- Cloud providers
- Companies which make tooling for AI, ML and Deep Learning
- 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
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#Community Sponsor
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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
AB
Amit Baldwa
@abaldwa
Blueprint for Building AI Products
Submitted Oct 18, 2019
Section:
Full talk
Technical level:
Intermediate
Session type:
Lecture
IT Product Development is changing at a rapid pace. From being an enabler of existing products, AI and ML has taken a Centerstage in Product development.
This talk is aimed at CIOs/Product Management folks and Data Scientists in creating a BluePrint of ‘Building AI Products’. It covers the improvements/changes required at each stage of Product Development for Building AI Products.
This talk also aims at providing the reasoning required by Data Scientists in propagating their ideas through the traditional organizations.
Outline #
- Introduce the Concept of ‘Pre-AI Products’ vs AI-Inside Products’ vs ‘AI-First Products’
- Key Ingrdients of a Success of a Product
- Discussion on when to use Machine Learning and when not to use.
- Ethical Design Principals
- Role of a Team in AI Product Development.
- Transition from an Pre-AI Product to AI-First Product
Requirements #
None
Speaker bio #
Amit Baldwa is Director Engineering at Finastra. A thought leader and strategist, with extensive leadership experience, Amit has spent significant portion of his career in Product Development, Amit is currently developing AI & Distributed Ledger Products.
A Data Sciences Enthusiast, Amit has implemented Supply Chain Analytics at Scale. His experience spans Fintech, Ecommerce, Retail, Supply Chain and Logistics. Amit mentors start-ups, young professionals and students on applicability of Artificial Intelligence, Data Science in their operations.
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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
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