Data Science: Sequential Data Modeling With LSTM

Organizer: Triangle SQL Server User Group
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• What we'll do
Long Short Term Memory (LSTM) is a type of recurrent neural network that can recognize and model dependencies in sequential data. LSTM is state of the art for natural language modeling, it is the brain behind Siri, Alexa and Google Now. In this talk, we will learn the basics of LSTM, how to use LSTM with Keras and finally how to choose architectures given different natural language problems, e.g. sentiment analysis, machine translation and intelligent chat bots.


Zhiming Zhang is a software engineer at Channeladvisor. He specializes in predictive analytics, machine learning and neural networks. Zhiming obtained his PhD degree in computer engineering from Iowa State University. He became really interested in neural networks while working on a project trying to improve the accuracy of using keystroke patterns for live authentication.

• What to bring

• Important to know


Poster: triangletech