Natural Language Processing with Attention Models (Coursera)

Natural Language Processing with Attention Models (Coursera)
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Natural Language Processing with Attention Models (Coursera)
This course is for students of machine learning or artificial intelligence as well as software engineers looking for a deeper understanding of how NLP models work and how to apply them.

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In Course 4 of the Natural Language Processing Specialization, offered by DeepLearning.AI, you will:

a) Translate complete English sentences into German using an encoder-decoder attention model,

b) Build a Transformer model to summarize text,

c) Use T5 and BERT models to perform question-answering, and

d) Build a chatbot using a Reformer model.

Course 4 of 4 in the Natural Language Processing Specialization


Syllabus


WEEK 1

Neural Machine Translation

Discover some of the shortcomings of a traditional seq2seq model and how to solve for them by adding an attention mechanism, then build a Neural Machine Translation model with Attention that translates English sentences into German.


WEEK 2

Text Summarization

Compare RNNs and other sequential models to the more modern Transformer architecture, then create a tool that generates text summaries.


WEEK 3

Question Answering

Explore transfer learning with state-of-the-art models like T5 and BERT, then build a model that can answer questions.


WEEK 4

Chatbot

Examine some unique challenges Transformer models face and their solutions, then build a chatbot using a Reformer model.



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