Deep Learning for Natural Language Processing

Level: Intermediate

Starting with the basics, this book teaches you how to choose from the various text pre- processing techniques and select the best model from the several neural network architectures for NLP issues.

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Key Features of this Deep Learning for Natural Language Processing Course:

After-course instructor coaching benefit
After-course computing sandbox included
Learning Tree end-of-course exam included

You Will Learn How To:

Understand various pre-processing techniques for deep learning problems
Build a vector representation of text using word2vec and GloVe
Create a named entity recognizer and parts-of-speech tagger with Apache OpenNLP
Build a machine translation model in Keras
Develop a text generation application using LSTM
Build a trigger word detection application using an attention model

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3-day instructor led training course
One-on-one after-course instructor coaching
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Standard $2650

Government $2355

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In Class & Live, Online Training

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Note: This course runs for 3 Days

Apr 1 - 3 9:00 AM - 4:30 PM EDT New York / Online (AnyWare) Reserve Your Seat
May 6 - 8 9:00 AM - 4:30 PM EDT Herndon, VA / Online (AnyWare) Reserve Your Seat
Jun 3 - 5 9:00 AM - 4:30 PM EDT Ottawa / Online (AnyWare) Reserve Your Seat
Jun 24 - 26 9:00 AM - 4:30 PM EDT New York / Online (AnyWare) Reserve Your Seat
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Sep 2 - 4 9:00 AM - 4:30 PM EDT Ottawa / Online (AnyWare) Reserve Your Seat
Sep 30 - Oct 2 9:00 AM - 4:30 PM EDT New York / Online (AnyWare) Reserve Your Seat
Nov 4 - 6 9:00 AM - 4:30 PM EST Herndon, VA / Online (AnyWare) Reserve Your Seat
Dec 2 - 4 9:00 AM - 4:30 PM EST Ottawa / Online (AnyWare) Reserve Your Seat

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Important Deep Learning for Natural Language Processing Course Information

Requirements

Strong working knowledge of Python, linear algebra, and machine learning is a must.
Who Should Attend This Course

If you’re an aspiring data scientist looking for an introduction to deep learning in the NLP domain, this is just the book for you.