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Bewertung und Feedback des Lernenden für Natural Language Processing with Attention Models von deeplearning.ai

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774 Bewertungen

Über den Kurs

In Course 4 of the Natural Language Processing Specialization, 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. By the end of this Specialization, you will have designed NLP applications that perform question-answering and sentiment analysis, created tools to translate languages and summarize text, and even built a chatbot! 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-Bewertungen

JH

4. Okt. 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

SB

20. Nov. 2020

The course is a very comprehensive one and covers all state-of-the-art techniques used in NLP. It's quite an advanced level course and a good python coding skill is a must.

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51 - 75 von 194 Bewertungen für Natural Language Processing with Attention Models

von martin k

26. Apr. 2021

Low quality programming assignments, but considering the price it's good overall

von Randall K

14. Juni 2021

In the previous 3 courses, the HW was a natural extention of the lectures and provided solid reinforcment of the course material. However, in this course, I found the courses did not prepare me for the HW. Furthermore, I found the lectures too terse, often incoherent, and the homework tried to introduce new concepts that were not discussed in the lectures. Also, the code in the labs was poorly organized and the lack of a consistent and coherent style between assignments and even previous courses, which made it difficult to follow the logic. I often spent a lot of time sorting out tensor indexing issues, which is very difficult in Jupyter without a debugger.

von Chenjie Y

18. Nov. 2020

I think the last course is a bit rush... Many concepts are not natural and cannot be explained by one or two sentences. Comparing to the previous courses in the specialisation which really explains concepts and intuitions in detail, this last course is a bit too rough. I would rather spend another month to study the materials in two courses, instead of staying up late to read papers and blogs to understand what was not explained clearly in the course. And also, i see that trax is a good library but i think up to now it is not yet mature, and i really wish all the assignments can have tensorflow versions and let the students to choose.

von DAVIDE M

9. März 2022

This course is good if you want to be theoretically good with Transformers model. I mean now I can explain those concepts to my colleagues or pair. It lacks with the practical parts, a lot of exercises are too guided e there is no project that you can show off. The hugginface part is the most interesting for practicing but there are only a few lessons. In the end, do not expect to make a chatbot in week four, it is "just" a model that generates dialogue between two persons.

von Lucky S

24. Feb. 2022

This Course is the weakest course of this Specialization.

Course 1 - 3 was very strong and solid. But Course 4 feels very rushed. The Curriculum is very hard to follow, let alone to understand. The Lab wasn't commented enough to give us proper explanation (Especially week 4). There are a lot of concept that isn't explained at great length when it should.

von Tianpei X

1. Nov. 2020

the homework is way too simplified esp. in week 3 and week 4. My impression is that the ungraded lab was actually the real homework but was put aside to allow more people to pass. That is not a good compromise.

von George G

6. Dez. 2020

Week 1 jumps into material that is better explained in Week 2. Attention deserves a more gradual and a more deep explanation. Weeks 3 and 4 cover a lot of ground, without going into depth.

von George L

11. Apr. 2021

Younes is a bad teacher. He may have good technical chops, but teaching is a different skill altogether. Overall, the NLP specialization design is much much worse compared with the DL Specialization. On one hand, you were taught a lot of stuff that are deep but cursory, on the other hand, the excises are either too difficult for you to get any clue or most of the time actually too simple and you only need to enter simple parameters, therefore cannot really learn anything! I really don't know why there are so many people giving 5 star rating!

von Dimitry I

17. Apr. 2021

Material coverage is very superficial. Do not expect to fully understand or be able to work with Attention models after doing this course.

Sadly, these types of courses and their fake near 5-star reviews are destroying Coursera.

von David M

22. Feb. 2021

Unfortunately, the classes are given at a very primitive level without explaining what exactly Attention models do. The programming exercises were not explained well, either

von Rabin A

19. Apr. 2021

The course was pretty good. It introduced me to the state-of-the-art algorithms and techniques needed to have a sound understanding of NLP. One thing I didn't like about the teaching method in the whole specialization is that Younes was the one teaching the course content to us but Łukasz talked as if it was he giving some of the lectures, although we could clearly find out it's Younes from his voice. Thanks especially to Younes for doing all the hard work for the specialization. You deserve a 5 star.

von Dustin Z

17. Dez. 2020

A very good and detailed course. Definitely the most challenging course I have taken by DL.ai. Gives a good overview of Transformers, the current cutting-edge of NLP models. Also, provides great insight into Trax, Google Brain's ML framework, which was helpful in understanding how deep learning frameworks are built. One of the teachers is one of the authors of Trax!

von Ganesh s m

10. Okt. 2020

Every week's assignment brings a new challenge and it was fun to complete the assignments. Course Instructors explain concepts very well. This course teaches you from the beginner level to a professional level. Covers every topic related to NLP. I enjoyed learning NLP with Deeplearning.ai. I would like to thank deeplearning.ai for making this course.

von Huu M T H

30. Sep. 2020

Good course in overall. The last two weeks' assignment is a little bit too light. The instructor could introduce more about loading pretrained models and fine-tune them as it is a popular practice nowadays for small companies with limited resources (data/computation). Introduction to "easy-to-use" framework such as huggingface is highly recommended.

von Rajendra A

30. Dez. 2020

This specialization covers from NLP basics to the advance models currently being used. All the programming assignments, contents and sessions were thoughtful. Exposure to Trax library and learning experience was really excellent. Thanks to the entire team of this specialization and coursera team.

von Peter T

1. Jan. 2022

​The final weeks of this course, especially, introduce cutting edge NLP models and practices, such as T5, Huggingface and Reformer. This entire course was comprehensive in breadth. Highly recommended but you should be prepared to put 10x more hours into it than the Coursera estimates.

von Long L

18. Nov. 2020

Thank you Coursera and the DeepLearning.AI team. The moment I set foot on this journey I did not think I would love NLP so much. The course is very informative: it teaches NLP from the very first naive algorithm to the State-of-the-art models today.

von Bharathi k N

12. Okt. 2020

The course is so good and well presented. I really enjoyed the whole specialization. Thank you for this amazing course and the whole specialization which that me a lot. Thank you Andrew NG and deeplearning.ai team for this amazing specialization.

von Alan K F G

21. Okt. 2020

I learnt a lot about Transformers and Reformers which belong to the most advenced models for NLP tasks. The instructors were fully prepared though I'd prefer to see more animations in following courses. Thank you so much for spreading knowledge!

von Muhammad T W

12. Juni 2021

This course has helped me a lot in developing my NLP skills and now I am confident that I can solve NLP problems easily because both the instructors Younes and Luckerz has thought this course in a way that it can be absorbed in any NLP problem.

von Patrick A

26. Nov. 2020

An excellent course that covers research that was published about two months early.

It doen't get more cutting edge than that, and the technology (reversible residual layers) is immediately applicable and a very powerful enabler.

Thanks a lot!

von vadim m

17. Okt. 2020

An amazing level of breadth and depth of the material presented. State of the art techniques are exemplified via carefully crafted lab assignments with sufficient hints for students to be able to comprehend hard technical concepts.

von Jim F

28. Feb. 2021

Thanks for setting out to do the impossible and creating this set of courses. You have opened a doorway to understanding where the state of the art is. The rest is up to me. That's the purpose of education.

von Simin F

27. Nov. 2020

Helpful and Interesting! This course leads me gradually understand how transformer works and being optimized along with several models without much confusions. Great thanks for the deeplearning.ai Team!!

von lonnie

23. Juni 2021

T​his 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.