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Learner Reviews & Feedback for Natural Language Processing with Attention Models by DeepLearning.AI
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About the Course
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 with a deep learning framework (e.g., TensorFlow, Keras), as well as proficiency in calculus, linear algebra, and statistics. Please make sure that you’ve completed course 3 - Natural Language Processing with Sequence Models - before starting this course.
This Specialization is designed and taught by two experts in NLP, machine learning, and deep learning. Younes Bensouda Mourri is an Instructor of AI at Stanford University who also helped build the Deep Learning Specialization. Łukasz Kaiser is a Staff Research Scientist at Google Brain and the co-author of Tensorflow, the Tensor2Tensor and Trax libraries, and the Transformer paper.
Top reviews
JH
Oct 4, 2020
Can the instructors make maybe a video explaining the ungraded lab? That will be useful. Other students find it difficult to understand both LSH attention layer ungraded lab. Thanks
LL
Jun 22, 2021
This course is briliant which talks about SOTA models such as Transformer, BERT. It would be better to have a Capstone Project. And entire projects can be downloaded easily.
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251 - 251 of 251 Reviews for Natural Language Processing with Attention Models
By Ignacio d l S
•Jan 8, 2022
Too easy. I can say I almost didn't learn anything.