Please join us with SK Reddy, AI and ML expert, as he delves into the magic of text summarization using deep neural networks. Using neural networks to summarize text has been a focus of many NLP experts. Many approaches were defined to test the capability of deep models to accurately summarize and still make sense. Summarization could be predominantly done in two different ways. In extraction approach, a neural model copies the words from the input to form a summary.

Interpreting deep learning and machine learning models is not just another regulatory burden to be overcome. Scientists, physicians, researchers, and analyst that use these technologies for their important work have the right to trust and understand their models and the answers they generate. This talk is an overview of several techniques for interpreting deep learning and machine learning models and telling stories from their results. Speaker: Patrick Hall is a Data Scientist and Product Engineer at H2O.ai. Prior to joining H2O, Patrick spent many years as a Senior Data Scientist SAS and has worked with many Fortune 500 companies on their data science and machine learning problems.