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Natural Language Processing in TensorFlow(으)로 돌아가기

deeplearning.ai의 Natural Language Processing in TensorFlow 학습자 리뷰 및 피드백

5,943개의 평가
926개의 리뷰

강좌 소개

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In Course 3 of the TensorFlow Specialization, you will build natural language processing systems using TensorFlow. You will learn to process text, including tokenizing and representing sentences as vectors, so that they can be input to a neural network. You’ll also learn to apply RNNs, GRUs, and LSTMs in TensorFlow. Finally, you’ll get to train an LSTM on existing text to create original poetry! The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization....

최상위 리뷰


2019년 8월 26일

Excellent. Isn't Laurence just great! Fantastically deep knowledge, easy learning style, very practical presentation. And funny! A pure joy, highly relevant and extremely useful of course. Thank you!


2020년 7월 21일

Great course for anyone interested in NLP! This course focuses on practical learning instead of overburdening students with theory. Would recommend this to every NLP beginner/enthusiast out there!!

필터링 기준:

Natural Language Processing in TensorFlow의 929개 리뷰 중 751~775

교육 기관: Luigi S

2019년 12월 26일

Nice and clear

교육 기관: LANKE N B J

2020년 6월 27일

good content

교육 기관: Abdur R

2021년 4월 12일

Best Course

교육 기관: Rohit K S

2020년 9월 19일


교육 기관: Ashwani Y

2020년 4월 22일

its good

교육 기관: Muhammad A

2021년 8월 23일

5 stars

교육 기관: Egi R T

2022년 7월 9일


교육 기관: Zayn K

2021년 7월 8일


교육 기관: Wellington B R

2020년 7월 24일


교육 기관: RAJAT S

2020년 6월 26일


교육 기관: Milad M

2020년 5월 15일


교육 기관: M n n

2020년 4월 16일


교육 기관: Amit K

2020년 5월 12일


교육 기관: Pablo A

2020년 9월 15일

After taking courses 1&2 of this Specialization I had high expectations for this course on NLP. I am a linguist learning ML so I was really hoping to learn a lot. However, this course has no graded assignments, which was a disappointment as I really enjoy the challenge that those present. Making the assignments not required really takes away from the experience imo. Additionally, the content seems kind of basic in this course. I feel like the first 3 weeks are spent doing mostly the same thing. It isn't until week 4 when we finally get to something somewhat interesting. I really wish this course was better structured. I will be checking out other NLP courses, but this one was a bit of a disappointment.

교육 기관: Jesus E R

2021년 3월 24일

Very, very basic course. It over-explains the simple things but glosses over important concepts and choices (choice of optimizers, choices of some layers, among others).

Additionally, the course is overly repetitive. Videos explain the same thing over and over. I understand this is more about Python and Tensorflow than is about ML but even then, we spend longer time explaining the non-TF parts of the code than on the TF parts and the reasoning behind them.

This course also lacks practice. Quizzes focus on the exact syntax for a function but not that much on the whys. It lacks programming exercises (first week has a very simple workbook that doesn't teach much).

교육 기관: Aditya L

2020년 9월 3일

This course has a lot of exciting material. However, it can be challenging and hard to work on if you are not comfortable with RNNs and LSTMs already. It cross-references to many videos of Andrew Ng, which would be ok, but when you see those videos you realize you need to learn more things and so on. Additionally, the assignment is ungraded which takes away some of the challenges. Definitely a good introduction but to get deeper meaning on this you have to do your own research and studies on the material quite a bit.

교육 기관: Albert Z

2021년 12월 12일

Not that bad, but should cover more details. For example, the num_words parameter in Tokenizer is actually len(word_index)+1, but the tutor does not mention that in the lecture. It troubles me a lot in the assignment until I finally figure that out by myself. I still recommend this course If you want to take the tensorflow certificate exam. But you need to learn more by yourself. You'd better read all the API documents for the commands mentioned in this course to make sure that you understand them correctly.

교육 기관: Corrie

2020년 2월 7일

Some lessons in this course were so repetitive that it seemed like a waste of time. Week 2, in particular, felt monotonous and really put a damper on my interest in the information. Despite there being some useful code to learn, Laurence talks though the code in video clips, and then does a screencast of himself talking through the same code in a workbook. I have really enjoyed the 2 courses prior to the NLP course in the TensorFlow in Practice Specialization, but this one seems less developed.

교육 기관: Asgeir S

2021년 3월 3일

The course material is good.

However, multiple URLs are outdated both in the course material and in coding exercises (which makes some coding exercises not working).

Optimally some of the coding exercises should be updated to newer versions of TensorFlow (some things from the 2.alpha version are no longer available in version 2.4.x and some things are deprecated).

Also, it would be great if the coding exercises were graded (like for earlier courses in this specialization).

교육 기관: Kevin H

2020년 5월 13일

The content is good, the videos well paced. The code examples are also very useful.

But I feel the structure of the class is too loose. In my opinion, it would benefit from having assignments that must be submitted and graded.

Maybe they could be small and focused - like focusing on just working with the tokenizer, or setting up Embedding layers or LSTM layers. There could also be one where you load a pretrained model and writing the next token prediction loop.

교육 기관: Ethan V

2019년 8월 25일

I'm a bit disappointed with this specialization overall. I think I expected a deeper familiarity with tensorflow, more exposure to the TFData abstraction for large datasets, more low-level exposure to extending your models to fit a specific problem in your domain. Instead I feel like this specialiaztion would better be titled "Black box manipulation of the Keras API". That's a shame, given how solid the first specialization was.

교육 기관: Brian D O

2021년 3월 17일

This course is out of date and not as polished as the Deep Learning specialization. Data urls in the notebooks are broken. The quizzes are mostly random parameter names that you would google if you needed them, and the week 4 quiz actually has duplicate questions from week 3. The coding exercises are not graded. I did them anyway because I want to learn, but I also want to be challenged and want a certificate that conveys rigor to employers.

교육 기관: Ravi V K

2020년 4월 7일

This could have been some more intense with 2 quiz in each week (1 or 2 tough questions), giving a written explanation of what a code snippet is meant for or each line of code is meant for, spend time on explaining fundamental concepts. Highlights of course, clear and crisp in explanation of concepts and functioning of code. overall, coherence is well appreciated.

교육 기관: Rajesh R

2021년 6월 20일

The models developed in the course of the instruction were pretty useless. The instructor didn't discuss enough about how these models could be improved. The content of the course doesn't allow you to actually take on proper NLP and deep learning projects in industry. The demands of the industry are quite different from what's covered in this course

교육 기관: luis a

2019년 10월 11일

In my opinion, the course was too simple. There are many many concepts that are not covered properly. Even if they recommend going to the deep learning course from Andrew, I believe that at least could explain a bit more some parameters used in the functions and how actually work.

On the other side, you make cool thinks like text generation!