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.
