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Leveraging Deep Learning for Natural Language Processing Course

Code: 1278 Category: Tag:

In this Natural Language Processing course, you will learn how to navigate the various text pre-processing techniques and select the best neural network architecture for Natural Language Processing.

Natural Language Processing Course Delivery Methods



Natural Language Processing Course Benefits

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, a deep learning API

Develop a text generation application using Long short-term memory (LSTM)

Build a trigger word detection application using an attention model

Test your knowledge in the included end-of-course exam

Continue learning and face new challenges with after-course one-on-one instructor coaching

Natural Language Processing Course Outline
Module 1: Introduction to Natural Language Processing

In this module, you will learn about:

The basics of Natural Language Processing and its applications
Popular text pre-processing techniques
Word2vec and Glove word embeddings Sentiment classification
Module 2: Applications of Natural Language Processing
Module 3: Introduction to Neural Networks
Module 4: Foundations of Convolutional Neural Networks (CNN)
Module 5: Recurrent Neural Networks (RNN)
Module 6: Gated Recurrent Units (GRU)
Module 7: Long Short-Term Memory (LSTM)
Module 8: State of the Art in Natural Language Processing
Module 9: A Practical NLP Project Workflow in an Organization

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