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Speaker "Sourav Mazumder" Details Back

 

Topic

How to operationalize Trustworthy AI Models in production

Abstract

Using AI for business solutions and operations has become mandatory for organizations today. Most of the organizations today are using various technologies and platforms to develop (and deploy) AI models based on choices and skills of data scientists in different groups. However, ensuring Trustworthiness of those AI Models is of paramount importance for every organization.for various reasons starting from social responsibility, compliance to legal compliance, audit requirements, to assurance of overall business value. The requirements to make an AI Model trustworthy run across the areas of Independent Validation of Models; Continuous Monitoring of Model Performance (Accuracy, Bias, Drift, etc) in Production; Model Interpretability; Controlled sourcing and reuse of Data, Features and Packages; Model Facts; Approval steps in Model Lifecycle; Change Management, etc. In this session you will learn how AI models developed and deployed in Heterogeneous platforms can be Operationalized keeping above requirements fulfilled but customized based on an organization's governance requirements. Attendees would also learn the technology agnostic key principles those can be used to ensure trustworthiness of AI Models.

Profile

Sourav is a Thought Leader in the area of Artificial Intelligence and Big Data for last 10 years with over 22 years of total IT experience. Sourav has consistently driven business innovation and values through Data Science Methodologies and Technologies transpired through his knowledge, insights, experience and influencing skills across multiple industries including Manufacturing, Insurance, Telecom, Banking, Media, Health Care and Retail industries in USA, Europe, Australia, Japan and India. In last 10 years he has influenced key decision makers in about 7 different fortune 500 companies to adopt Data Science technologies to address complex business needs through use of large volume of Data. Sourav has also consistently provided directions to and successfully led numerous challenging Data Science oriented projects in last 10 years applying various Data Science methodologies ranging from Descriptive statistics, Probabilistic Modeling, Algorithmic Modeling, NLP, etc., to solve critical business problems using large volume of data. Sourav is a seasoned professional experienced in working both as an individual contributor and team player thriving in a dynamic and ambiguous environment. Sourav has experience and exposure in working in variety of Data Science and Big Data related technologies like Watson APIs, Watson Studio/DSx, Watson Explorer, Spark, Hadoop, BigSQL, HBase, MongoDb, Solr, System ML, Brunel, Cognos, R, Python, Scala/Java, etc., using them in projects involving phases from PoC to Productionization. Sourav consistently publishes papers/blogs/articles in various industry forums. He also speaks in various Industry conferences on Data Science use cases and Big Data.