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学生对 deeplearning.ai 提供的 Natural Language Processing in TensorFlow 的评价和反馈

4.6
5,774 个评分
903 条评论

课程概述

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 deeplearning.ai 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 deeplearning.ai 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....

热门审阅

GS
Aug 26, 2019

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!

AS
Jul 21, 2020

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!!

筛选依据:

751 - Natural Language Processing in TensorFlow 的 775 个评论(共 906 个)

创建者 Asgeir S

Mar 3, 2021

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However, multiple URLs are outdated both in the course material and in coding exercises (which makes some coding exercises not working).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

创建者 Kevin H

May 13, 2020

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.

创建者 Ethan V

Aug 25, 2019

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 deeplearning.ai specialization was.

创建者 Brian D O

Mar 17, 2021

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.

创建者 Ravi V K

Apr 7, 2020

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.

创建者 Rajesh R

Jun 20, 2021

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

创建者 luis a

Oct 11, 2019

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!

创建者 Sina D

Apr 19, 2020

This course does not follow the same standards as the previous courses from deaplearning.ai. The material taught in this course are two basic and do not go in-depth to introduce the major techniques that are being used in the field. The colab notebooks are not provided in most cases and you have to look for them in QA or Github.

创建者 Stefan B

Apr 12, 2020

In the previous two courses of the specialization, coding exercises were compulsory and graded. In this course, all coding exercises were voluntarily and not well documented. It seemed to me that for whatever reason, the makers of course 3 (natural language processing in tf) put less effort into the making. Bit disappointed.

创建者 Giorgos F

Mar 4, 2021

A good course overall, however the explanations offered on convolutions, LSTMs, GRUs were a bit poor. I know it is beyond the scope of the course, but it will help the student to know what an LSTM is overall and what is the meaning of different arguments (i.e., the `return_sequences` argument in LSTM class).

创建者 janmejay b

Sep 18, 2020

Basic concepts of NLP. I expect more from this course . Not helpful for real world problem. Should have add more content with more complex and real world problems with programing exercises. No assignments for evaluation of a student understanding. This is not expected from Deeplearning.ai.

创建者 Dustin Z

Jun 27, 2020

It was a good course like the rest in the series, though in this course, they don't link to the colab notebooks that Lawrence works through in the items for each week. The colab notebooks exist on lawrence's colab account but you need to hunt them down. I would suggest fixing this oversight.

创建者 José D

Apr 20, 2020

This third course provides main NLP concepts using Keras simple example codes. Just like Courses 1 & 2, there's no math and as explained in the videos, if you want a deeper understanding, then you want the "Deep Learning" specialization. Only quizzes, no graded exercises for this course

创建者 J E

May 2, 2020

It was good but there are several errors in the code for some weekly exercises.

I wanted to raise a PR in the author's Github repo to fix theses. However, upon seeing the backlog unaddressed PRs in the author's Github repo, I didn't bother as they will probably not be looked at.

创建者 Ramón W

Oct 13, 2021

The length of the videos is fine. Personally, it bothered me that there were no programming tasks, the quizzes were too short and some of the questions were repetitive. I would have liked to see programming tasks, more quizzes and also intermediate questions in the videos.

创建者 Rajat Y

Nov 30, 2019

Since the course doesn't mention "Introduction" to NLP, I thought that the course will provide a detail insights to Natural Language Processing but the course only covers basics of it. Also as far as tensorflow is concerned I was expecting more hands-on experience in it.

创建者 Ignacio L

Feb 12, 2021

the lack of graded exercise makes this course somewhat messy. Many of the codes that are given to analyze don't work on the go. The back and forth between sets and cases of classification in my case at least, did not help to fully grasp what was going on.

创建者 afshin m

Jan 17, 2020

week 2 and week3 are disorganized - the examples don't run without making modifications based on information in the forums.

However the overall course is worth it. I hope they pay more attention to making the examples accessible and making them work.

创建者 Peter-John H

Oct 2, 2021

This course did not require lab submissions which I really liked because it coerced and helped me by providing an objective to learn more. It also introducted topics such as LTSM, Global average pooling and regulizers which I feel were too rush

创建者 Thusitha C

Aug 1, 2020

Nothing against the instructor, he was really nice. But the content is extremely basic, to the extent that the whole course could be completed in one day. At least the previous courses had graded assignments, but this one was way too easy.

创建者 PRATIK K C

May 23, 2020

One example in case of text classification could have been theoretically worked out. For example classification using RNN/LSTM. How a word vector is passed as input to one unit of lstm? To view in on paper would make concepts more clear.

创建者 Hector B

Jun 6, 2020

The course is good but lacks graded coding homeworks, these are the most powerful learning tools and it involves reflecting upon the matter, even if they have bugs or version mismatches, they are the most important learing tool!

创建者 Pandu D

Oct 15, 2021

Please give an explanation for each code in colab like in teh previous course. Moving between expalantion video tab and colab tab was troublesome. Moreover, there are some labs that contain an error which is predict_classes().

创建者 Reem

Apr 1, 2020

Good overview but the assignments seem a bit disconnected from the classes at times (e.g. when asking us to use regularizers). Transformers are a lot more popular now and they were not touched on in the course.

创建者 Chidvilas K R

Oct 25, 2020

There was no continuity in the videos. Felt it could have been much better. And the level of course is too low. You should change the title to "Basics of Natural Language Processing in TensorFlow".