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    Back to Natural Language Processing with Sequence Models

    Learner Reviews & Feedback for Natural Language Processing with Sequence Models by DeepLearning.AI

    Filled StarFilled StarFilled StarFilled StarHalf Faded Star
    4.5
    stars
    1,169 ratings

    About the Course

    In Course 3 of the Natural Language Processing Specialization, you will: a) Train a neural network with word embeddings to perform sentiment
    analysis of tweets, b) Generate synthetic Shakespeare text using a Gated Recurrent Unit (GRU) language model, c) Train a recurrent neural
    network to perform named entity recognition (NER) using LSTMs with linear layers, and d) Use so-called ‘Siamese’ LSTM models to compare
    questions in a corpus and identify those that are worded differently but have the same meaning. By the end of this Specialization, you will
    have designed NLP applications that perform question-answering and sentiment analysis, created tools to translate language...
    ...

    Top reviews

    SA

    Sep 28, 2020

    Filled StarFilled StarFilled StarFilled StarFilled Star

    Overall it was great a course. A little bit weak in theory. I think for practical purposes whatever was sufficient. The detection of Question duplication was a very much cool model. I enjoy it a lot.

    AB

    Nov 12, 2021

    Filled StarFilled StarFilled StarFilled StarFilled Star

    This is the third course of NLP Specialization. This was a great course and the instructors was amazing. I really learned and understand everything they thought like LSTM, GRU, Siamese Networks etc.

    Filter by:

    151 - 175 of 240 Reviews for Natural Language Processing with Sequence Models

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    By larawang

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    May 7, 2022

    Thank you!

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Chen

    •

    Oct 27, 2021

    Thank you!

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Onuigwe V

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    Aug 29, 2020

    Excellence

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Daniel R

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    Oct 20, 2023

    Excelent!

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Pema W

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    Nov 11, 2022

    Very Good

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Oleg P

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    Nov 6, 2022

    All good.

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Justin H

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    Jul 12, 2023

    Brutal.

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Quan T H

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    Jul 19, 2022

    Awesome

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Zoizou A

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    Oct 25, 2020

    amazing

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Yongxin W

    •

    Oct 2, 2020

    so cool

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Rifat R

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    Sep 23, 2020

    Awesome

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Jeff D

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    Nov 15, 2020

    Thanks

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By MOURAD B

    •

    Apr 22, 2021

    goood

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Ricardo F

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    Jan 16, 2021

    Grear

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Nguyen H T T ( H

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    Apr 2, 2024

    good

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Asyraf I H

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    Jul 11, 2022

    Good

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By M n n

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    Nov 22, 2020

    Nice

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Saoudi H

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    Sep 28, 2020

    good

    Filled StarFilled StarFilled StarFilled StarStar

    By Dave J

    •

    Feb 15, 2021

    There are lots of good points. The instructors are knowledgeable, Lukasz Kaiser is one of the authors of Tensorflow and Trax. The material is generally presented in a clear way. The labs and assignments work smoothly. You learn how to implement significant NLP tasks in a modern framework (Trax).

    There are areas where I felt the course could have been better.

    The amount of taught material is only about half an hour of lecture per week. I felt that it covered the bare minimum to get you through the assignments but I would have liked a lot more content, going in more depth into the concepts and how the performance of the models discussed compares to state-of the-art models and how it could be improved.

    Having already done the Deep Learning Specialization, I was disappointed that this course did not build on that as a foundation. There is a lot of overlap between this course and course 5 of the DL Specialization, Sequence Models. To me, it would have made more sense to make that course a prerequisite, thus avoiding all the duplicated material and instead going beyond it.

    The other area where there's some room for improvement, though it's not at all bad, is the teaching style, which is mostly reading from a script. I would like to see more effort to engage with the learner and think about what they might need to progress on their learning journey. For example, discuss the strengths and weaknesses of an approach and where it fits into the history and state of the art of the subject; anticipate questions or likely misunderstandings and try to cover them or point to supplementary material.

    Overall, a good course that could have been a great course.

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    By D. R

    •

    Mar 22, 2021

    I'm a master/graduate student who took an NLP course in Uni.

    I think that overall this is a very a good introduction to the topic. Some concepts are really well explained - in a simple manner and with a lot of jupyter-lab code to experiment with.

    In general in this specialization - the first 3 courses are good. There are some quirks (e.g. why Lukas is needed at all? He doesn't really teaches, just passes it on to Younes) but nevertheless I learned from it. And I think they have good value in them.

    The 4th one, however, is completely disappointing. First 2 "weeks" are confusing, not really well explained, but somewhat "bearable". The last 2 weeks are complete sham. They claim to teach "BERT" and "T5" but don't really give any value. You're better off going elsewhere to learn these concepts.

    If it wasn't for this, I would give the overall experience a 5 stars, but because of this, I think the overall is more like 3 or 4.

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    By Sarkis K

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    Apr 17, 2023

    The courses have really enlightened me on NLP. I had no idea about the techniques. I'll give it 4 stars, because the course instructors have a monotonicity of lecturing as if reading from a teleprompter with a fake synthetic voice. It sometimes gives me a headache and I end up muting the videos and just reading the subtitles (which a lot of times don't make sense and are short paces so I have to freeze the screen, and open 2 other windows and read the lower caption text). I have been doing many courses on this platforms, and even though the instructors are on the top of their fields, but the way they deliver the courses is just "sometimes" and "not always" painful. I am sure this is not how they teach there own classes, especially in Stanford. Even though the course is 50$ per month, a think it won't cost the instructors much to show some authentic enthusiasm.

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    By Kostyantyn B

    •

    Nov 15, 2020

    The course is quite informative and it focuses on some cutting edge developments in NLP, which is great. I also really appreciated how well the instructors managed to explain the important concepts of GRU and LSTM. However, I wish the assignments were a bit more challenging. Most of the time, they felt like step-by-step instructions that are almost impossible to get wrong, with not much room for imagination. Good for self-esteem, not so good for skill building... Still, this was by no means a waste of time. A good foundational course that leaves you hungry for more. So perhaps it was the instructors' intention all alone to make it this way :)

    Filled StarFilled StarFilled StarFilled StarStar

    By Laurence G

    •

    Mar 22, 2021

    Better then the first two courses. Excellent week 1 introduction to Trax - I especially enjoyed Lukasz video about the origins, along with the links to source code and extra readings. Much of the technical content in weeks 2-4 is better covered in the deep learning specialization, however it's fairly brief and demonstrated using Trax so I still learnt something new. The applications in the assignments are interesting - the comparison between RNNs and n-gram models when doing text generation, parts of speech tagging and the question answer duplicate detection with Siamese models. Also got to try a few new things with numpy which was nice.

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    By Saurabh D

    •

    Aug 11, 2020

    To begin with, the course is very well structured and the assignments make you apply the theory what you have learnt in the videos in an effective way. The community on slack is very helpful if you need any help. The only thing that I didn't like was the course assignments were using *trax* for building the models instead of powerful frameworks like tensorflow, pytorch. That's the only reason I am rating 4 instead of 5 stars. Overall it is a pretty nice course and you will find it very easy if you have completed the Sequence models course from Andrew Ng's Deep learning specialization.

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    By Feng J

    •

    Feb 7, 2021

    This is a great course for natural language processing ! The video is short buy very precise for the concept. I think this is a middle level course, so one should already have the basic knowledge of deep neural network, and python skill. Then you will enjoy this journey. I hope for a more freedom style in coding assignment, rather than fill in the None parts style. Then we could obtain a solid knowledge by the deep practice. All in all, this is a great NLP course !!!

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