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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
5,354 个评分
841 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:

726 - Natural Language Processing in TensorFlow 的 750 个评论(共 837 个)

创建者 Lautaro R S

May 4, 2020

Not as good as the previous courses of the specialization. It is not as engaging, maybe it is the lack of rated exercises, but maybe also the contents are not taught as well as previously.

创建者 Robert K

Aug 18, 2019

Too basic for me. I was hoping for some nice hands-on Tensorflow (not Keras) tutorials. Some deeper modeling and understanding. Good for children :), although they now know more than me.

创建者 Andreas F

Jan 14, 2021

Overall a good course. Would like to see more commentary in the notebooks though. Furthermore, in my opinion, no Python2 code or deprecated functions of keras/tensorflow should be used

创建者 Purnendu S

Sep 20, 2020

Good And Clear Lectures , But Programing Exercises Are Ungraded And The Week Quiz Questions Are Too Easy , I Felt Like Its Less Like Learning And More Like Rushing To Complete Course

创建者 曹杰

May 30, 2020

I got the basic idea behind the sequence models while lots of code shown in the course are used to deal with the text and prepare for the training, which leaves a huge knowledge gap.

创建者 Ankit G

Jun 20, 2020

I guess there should have been a bit more explanation of the techniques used to provide a bit more understanding rather than just skimming from 50000 ft instaed of atleast 20000 ft.

创建者 Phung T

Feb 19, 2021

The first two courses of the series were awesome, but this course is quite a let down imo. There is no graded lab, the content feels pretty rush and it feels quite lacking

创建者 David R C S

Jan 6, 2021

Good course to introduce to the NLP world, but it lacks explanations, so you have to complement this with other sources even for understanding what you are doing here.

创建者 Davide C

Aug 3, 2020

Very superficial and requires no exercise to be solved so it is up to you to learn anything.

There are many topic that feel unfinished, many examples that are unsolved.

创建者 Piyush J

May 10, 2020

There were some prerequisites of the course related to deeplearning, which should have been known, then the course would have been understood better.

创建者 Roberto F

May 25, 2020

This course was really useful. You always work from a practical point of view, although there are not enough exercises to acquire a remarkable ease.

创建者 Adam I

May 10, 2020

I was expecting a complete course to master tensorflow but Laurence barely taught tensorflow in this specialization. It was more of introduction.

创建者 Suhan A

Apr 17, 2020

There weren't any graded Exercise like other courses, which would've made us think a lot more.

I hope they add graded exercise to this course.

创建者 Yevhen D

Feb 4, 2021

The course is too simple and doesn't cover topics deep enough. I suggest adding more practical assignments and explaining LSTM, Embedding etc

创建者 Christopher C

Nov 30, 2020

Introduction to calling the different functions is fine but there could be more focus on choosing parameters. The course feels too shallow.

创建者 Ana R

Jul 1, 2020

It's shallow, does not explain some important concepts. Seems like it was explained on a rush, or didn't bother going more into detaisl.

创建者 Guillermo M

Apr 8, 2020

I would like to implement programming exersice with rate because you can discuss with all the community and you enrich your knowledge.

创建者 naren d

Mar 2, 2021

Tutorials are difficult to navigate. Information about how to code is quite good. Hope they can improve their tutorial sections

创建者 Chad G

Feb 17, 2021

Good high level understanding of NLP, but not great implementation explanations and almost all of the links lead to a 404 error

创建者 Rohan L

May 24, 2020

Good starter course for NLP with Keras. But, I'd say doing Sequence Models ie C5 of the Deep Learning specialization is a must!

创建者 Marc-Antoine G

Nov 13, 2019

Please make the "Ungraded assignment" Graded and add more comments/directive in them to make sure we understand each steps.

创建者 J N B P

Feb 1, 2021

This course shows the tools used for NLP in Tensorflow, it would benefit only those who have basic knowledge of NLP.

创建者 Vera P

Jan 27, 2020

It's ok and certainly takes less time than expected, but it's a shame that there are not coding graded exercises.

创建者 Wayne Y

Apr 15, 2020

I feel that the course content is lacking in depth. Usually a week of materials can be finished in a few hours.

创建者 Meraj Z

Jan 18, 2020

Detailed Description is still missing, makes you sometime to google and find the exact understanding.