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Overview
In Course 4 of the Natural Language Processing Specialization, you will: a) Translate complete English sentences into Portuguese using an encoder-decoder attention model, b) Build a Transformer model to summarize text, c) Use T5 and BERT models to perform question-answering. By the end of this Specialization, you will have designed NLP applications that perform question-answering and sentiment analysis, and created tools to translate languages and summarize text! Learners should have a working knowledge of machine learning, intermediate Python including experience...
Syllabus
- 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.
- Text Summarization
- Compare RNNs and other sequential models to the more modern Transformer architecture, then create a tool that generates text summaries.
- Question Answering
- Explore transfer learning with state-of-the-art models like T5 and BERT, then build a model that can answer questions.
DeepLearning.AI via Coursera
2 hours 28 minutes
Paid Certificate Available
English
On-Demand
Intermediate
Instructor
Younes Bensouda Mourri
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