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
In-Person
Online
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
العربية