ML Models to Products: Challenges Building Products Using ML

This session will talk about two real-world case studies of AI based solutions followed by an overview of the challenges involved in productionizing ML based solutions. We will then go over the Machine Learning product lifecycle, how it is different from the traditional software development cycle, the various stakeholders involved, their  roles and responsibilities in building ML based products.


KEY TAKEAWAYS

• Building products using ML is a very iterative process
• Make models for products as simple as possible, but no simpler.
• To create real impact, It is important to measure the right metrics

ABOUT THE SPEAKER
Lavanya is a Machine Learning Scientist and an Entrepreneur. She holds a PhD in Machine Learning from the Indian Institute of Science and a masters in Computer Graphics from the University of Utah. She is  the founder of MachineLearningInterview.com that focuses on AI based assessments and data science interview prep. She has worked in the industry in a variety of roles at Amazon(Seattle and Bangalore), InMobi, Myntra(early-employee) and Kenome.io (a deep-tech NLU startup where she handled Product). She has also worked on collaborative projects with organizations such as Xerox Research Labs, IBM Research Labs, NetApp during her PhD and is the author of several peer-reviewed papers in top conferences and journals.