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Text Prediction Using Recurrent Neural Networks with TensorFlow

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TensorFlow webinar: Text Prediction Using Recurrent Neural Networks and TensorFlow

April 26 @ 10:00 am - 11:00 am

Are you willing to learn how to perform text prediction using deep learning and TensorFlow?

Watch the video
to learn more!

Overview

In this webinar, Dipendra Jha and Reda Al-Bahrani demonstrated how to use Sequence-to-sequence decoder from TensorFlow library build using Long Short Term Memory (LSTM) cells, on top of the text inputs embedded using the embedding lookup available in TensorFlow.

You will learn about:
  • the required steps to accomplish text prediction from input processing, embeddings, to using LSTMs to make the prediction
  • the concepts of Recurrent Neural Networks (RNNs) and Long Short Term Memory (LSTMs), followed by coding and demonstration for accomplishing the acutal text prediction using TensorFlow.
The slides and code can be found here.

Who should watch?

This webinar will be of interest to Data Scientists, Software Engineers and Entrepreneurs in the areas of Connected Cars, Internet of Things/Industrial Internet, Medical Devices, Financial Technology (blockchain) and predictive apps/APIs of all sorts.

About the Presenters
Dipendra Jha
Dipendra Jha is a fourth-year Ph.D. Candidate in Computer Engineering at Northwestern University. He is exploring the field of Deep Learning and Machine Learning using High Performance Computing (HPC) systems in the CUCIS lab under Prof. Alok Choudhary. His research focuses on scaling up deep learning and machine learning models using HPC system, and their application to accelerate Materials Discovery in the field of Materials Science and Engineering. Prior to this, he completed his Master’s in Computer Science from Northwestern University.


Reda Al-Bahrani
Reda Al-Bahrani is a Ph.D. Candidate in Computer Science from Northwestern University. He is exploring the field of Deep Learning and Machine Learning in the CUCIS lab under Prof. Alok Choudhary. His research focuses on knowledge discovery for health informatics from structured data and textual data. He worked in IT infrastructure support at Saudi Aramco and on XHQ an Operations Intelligence Software at Siemens Saudi Arabia before joining the CUCIS lab. Before this, he completed his Master’s in E-Commerce Technology from DePaul University.

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