Natural Language Processing with TensorFlow

Parthiban Srinivasan (~parthisrini)




Natural language processing (NLP) involves the application of machine learning and other statistical techniques to derive insights from human language. With large volumes of data exchanged as text (in the form of documents, tweets, email, chat, and so on), NLP techniques are indispensable to modern intelligent applications. The applications range from enterprise to pedestrian. We will give a high-level overview of TensorFlow and its use in deploying deep learning systems. In other words, we will present examples that depict how TensorFlow can be utilized to carry out some of the NLP tasks, such as word embedding, language modeling, part-of-speech tagging and name-entity recognition.



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Parthiban Srinivasan earned his PhD from Indian Institute of Science, specializing in Computational Modeling and Simulation. He holds dual Masters Degree- one in Science and the other in Engineering. After his PhD, he continued the research at NASA Ames Research Center (USA) and Weizmann Institute of Science (Israel). Then he worked at AstraZeneca and two of the India’ leading contract research organizations, Jubilant Biosys and GVKBIO, before he floated the company, Parthys Reverse Informatics. Now his recent venture is VINGYANI, a company that specializes in machine learning and deep learning solutions for big data. Parthi is part of the Big Dive 6 class, a data science course for five weeks in Italy (

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Section: Scientific Computing
Type: Talks
Target Audience: Intermediate
Last Updated:

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