Keynote: DataOps – Value Realization in Data & Analytics Transformation
As enterprises continue to amass data at exponential rates it’s become more imperative to unlock its value.
Traditional approaches to data and analytics transformations have seen high failure rates — or never achieve their full potential.
In this session, BMC Chief Technology Officer Ram Chakravarti shares a recipe for success that rapidly turns new insights into fully operationalized production deliverables – all designed to unlock tangible business value from data.
In an aspiration to understand the whole world and make your instantly available assistant, Alexa, a reliable advisor and companion, we need to understand and extract wide-range of knowledge from information at a very large scale.
We need techniques for processing and understanding natural language to keep the knowledge fresh, and expand both qualitatively and quantitatively.
In this talk, we will walk you through the process of how Alexa, the voice-based assistant, learns to be more intelligent, natural and fun for everyone, everywhere.
. Siffi Singh, Software Development Engineer, Amazon
Data Solution Presentation
Details to follow…
Afternoon Keynote: Working smarter not harder – Transforming your business post-pandemic
Why you should be digitalising your business processes
Keeping your workforce online in the ‘new normal’
Increase predictability and performance through improved communication
Optimizing Platforms for Multiple Objectives with ML
Multi-sided platforms have witnessed an explosive growth by facilitating efficient interactions between multiple stakeholders, including e.g. buyers and retailers (Amazon), guests and hosts (AirBnb), riders and drivers (Uber), and listeners and artists (Spotify). A large number of such platforms rely on machine learning powered matching engines connecting consumers with suppliers by acting as a central platform, thereby finding the right fit and efficiently mediating interactions between the two sides.
In this talk we discuss a number of problems which need to be addressed when developing a search & recommendation framework powering multi-stakeholder platforms. We begin by describing a contextual bandit model developed for serving explainable music recommendations to users and showcase the need for explicitly considering supplier-centric objectives during optimization.
We highlight the importance of a multi-objective ranking/recommendation and discuss different ways in which stakeholders specify their objectives. Finally, we demonstrate how enhanced user and content understanding helps us in developing better models to power multi-stakeholder platforms.
. Rishabh Mehrotra, Staff Research Scientist & Research Lead, Spotify
Data Solution Presentation 2
Details to follow…
End of Conference
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