Walk the talk. Make info extraction from conversations intuitive & intelligent.
Details
What if you could process a conversation end to end, understand various contexts within the conversation, and generate actionable insights for your business based on this understanding?
We will talk about a solution built-in 3 modules. The first module consists of data generation using a state machine approach and data pre-processing. The second module consists of sentence class prediction and entity class prediction, whose outputs are then passed onto the third module. These outputs are then used in the third module to establish context and extract the required information.
About the speaker:
Oshin Anand
Ph.D. in MIS (Text Analysis, NLP) from IIM R, with expertise in mathematical and econometric modeling. Demonstrated experience with the public sector, government think-tanks, and global organizations. Over the years, Oshin Anand has managed automation as well as business analytics assignments in the data modeling domain, managed clients with wide-ranging challenges and helmed science teams.
Walk the talk. Make info extraction from conversations intuitive & intelligent.