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Natural Language Processing in TensorFlow

Natural Language Processing in TensorFlow

Data Science Training

 In this class, we will look at Natural Language Processing (NLP) and how to apply deep learning to practical NLP applications. Specifically, we will look at recurrent neural networks and its applications.

This is an advanced deep learning course. It assumes you have basic knowledge of deep learning and some hands-on experience with TensorFlow.

 This class will take you through the fundamentals of deep learning methods, with hands-on exercises. It also gives you broad understanding of NLP applications where deep learning can be used. The course is divided into 3 major components:

  1.  Fundamentals of Recurrent Neural Networks
  2.  Practical applications of NLP with RNN
  3.  Building an end-to-end NLP application

By the end of this class, you would have solid understanding of Recurrent Neural Networks, and how to use it for NLP problems. You will have confidence to build an end-to-end NLP application with deep learning.

Prerequisite of this class:

     Hands-on experience with Deep learning and TensorFlow 

 Course outline:

  1. Introduction to Natural Language processing.
  2. Deep dive into Recurrent Neural Networks, particularly LSTM
  3. Applications of deep learning in NLP domains: We will review named entity detection, text summarization, machine translation, and question answering systems
  4. A complete text processing pipeline
  5. Hands on exercises on creating an end-to-end NLP application in TensorFlow

All coding is done in TensorFlow and Python.

You will have access to an AWS machine where you can play and code with TensorFlow. TensorFlow is pre-installed by the course instructor.

Instructor for this course:

Junling Hu, a leading expert in artificial intelligence and data science, founder of question.ai, has built natural language applications based on deep learning. She is the author of an upcoming book on artificial intelligence and deep learning. She has worked in Samsung, PayPal and eBay where she led teams in building big data applications. 

What to bring:

Your Laptop.

Lunch will be provided.

Cancellation policy: The ticket is refundable up until 3 days before the class.

100% Money back guarantee. If you are unhappy after attending the class, you can ask for a full refund by writing to the organizer. (For administrative reasons, refund request needs to be filed within 24 hours after the event.)

Later Event: December 1
MedTech Demo Night at TechCode