Speaker "Divya Beeram" Details Back



Image Quality Assessment using Deep Learning


In this talk, I will give a brief overview on how convolutional neural nets work using Tensor Flow for image classification in a scalable environment. For this session, I will be using an image classification project at Intuit as a case study. At Intuit, we work with highly secure customer tax and accounting data, this creates multiple challenges on how to process/store data and be policy compliant.

This talk will focus on (a) Brief overview of neural nets (b) Convolutional neural nets with Tensor flow (c) Identifying the right network architecture for a business problem (d) Evaluation of the model performance and A/B testing in production. (e) Challenges and Learnings


Divya Beeram is a Data Scientist at Intuit; she has worked with Consumer Tax group on entity resolution problems using text mining and user behavior prediction models. Currently, Divya is working with Small Business group and is involved in building predictive models to understand and help small businesses with their financial needs. Divya has a Masters in Software Engineering.