arrow_back Dataset Denoising : Improving Accuracy of NLP Classifier
Taking AI Products to Market
Submitted by Puneeth N (@puneethnarayana) on Tuesday, 30 April 2019
Section: Birds Of Feather (BOF) session Technical level: Intermediate Session type: Lecture
Want to have specific focussed discussion on what it takes to take pure play AI products to market. Have first hand experience taking multiple AI products to Indian B2B Market, I wanted to get product managers and KBLs in the domain to come in and share their journey and experiences. Hence, suggesting a bird of feather session.
Session will shed light over all stages of the AI product development and how it differs from regular software developement.
Right from conceptualization, to data collection, annotation, repeated model tweaking, and model deployments.
Handling pure play AI and Data Science products has it’s own life cycle.
I want to share 2 such experiences that I have had over the past 3 years.
- What constitutes a AI product?
- Steps of Creating an AI product
- Learning to Swim, what happens when you put the product in the field.
- Lessons from the Indian Market
- Dealing with various stakeholders
- Key Takeaways
Puneeth is a quintessential technologist, with a zest for converting awesome innovations into great products. Having started off his career at Accenture Tech Labs over 5 years ago, Puneeth has focussed exclusively on products related to data domains and technologies. Through his career, he has donned various hats as a Data Engineer, Scientist, BI Consultant, AI Product Analyst, Co-founder and Product Manager. His most recent engagement has been to help SigTuple scale their flagship AI product in diagnostics.
Puneeth has a Masters degree in Computer Science from IIIT Bangalore.