So you want to build a chatbot? One that is humanized, has contextual responses, and can simulate true empathy for the end users. Where do you start? Andrew Mattarella-Micke is a firm believer that a great chatbot first starts with your data. Andrew shares how Intuit’s data science team preps, cleans, organizes, and augments training data along with best practices he’s learned along the way. Andrew also discusses the unexpected sources of data and how to use data to train your chatbots for context, how to review your data to identify the blind spots, and when not to use a chatbot for your user. You’ll discover the importance of other key considerations such as cultural and language differences across demographics as well.
Andrew Mattarella-Micke is a senior data scientist at Intuit, specializing in deep learning for NLP applications. Previously, Andrew was a postdoctoral fellow at Vanderbilt and Stanford, where he studied the brain networks underlying mathematical development. He holds a PhD in cognitive neuroscience from the University of Chicago.
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