Chevron Left
Natural Language Processing in TensorFlow(으)로 돌아가기

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

4.6
별점
4,522개의 평가
697개의 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 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....

최상위 리뷰

GS

Aug 27, 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 22, 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!!

필터링 기준:

Natural Language Processing in TensorFlow의 694개 리뷰 중 651~675

교육 기관: Igors K

Nov 21, 2019

No practical exercises that one must do

교육 기관: Shubham A G

Aug 31, 2019

A bit too easy and no real assignments

교육 기관: Yuxuan C

Apr 13, 2020

I wish there were graded assignments.

교육 기관: Ashwin H

Apr 25, 2020

Coding assignments are much needed!

교육 기관: Ahmed O M

Sep 14, 2020

Assignments need some improvment.

교육 기관: SUMIT V

May 29, 2020

not enough programming exercises

교육 기관: Giuseppe d M

Jul 19, 2020

Concepts explained too quiclky

교육 기관: Salem S

Apr 16, 2020

Code should be explained more

교육 기관: albert

Jun 20, 2020

Not challenging enough....

교육 기관: Ankit G

May 17, 2020

No programming assignments

교육 기관: Leon V

Jun 13, 2020

Force me to write code.

교육 기관: Artem K

Oct 06, 2020

Need more practice

교육 기관: Vikas C

Dec 24, 2019

Good course

교육 기관: Hamzeh A

Aug 20, 2019

good

교육 기관: Li P Z

Feb 29, 2020

Very disappointed in this course. Instructor seems to have limited understanding of how sequence models and word embeddings work, or is unable to communicate the ideas in his teaching. Explanation for the theory is limited, and he has difficulty tying theory to the TensorFlow framework. Not sure why you would begin teaching sequence models with LSTM blocks combined with standard NN, way too complex structure. Instructor doesn't talk about why sequence models are important and useful in the first place. Very very poor.

교육 기관: Mohamed A S

Apr 08, 2020

Instead of taking this course, I could've read the tutorials on the TensorFlow site. Those tutorials are regularly updated, maintained, much more detailed and they're FREE.

This course, along the other courses in this specialization are not good for other than exposition to the TF API. Actually, they're not even good at that because the TF tutorials do a much better job at that.

And it's so frustrating that over-fitting is never tackled in any way and not even a hint at how to solve it is even given.

교육 기관: Sebastian F

Aug 09, 2019

This was by far the hardest course on the sequence. I actually skip it and did courses on order 1, 2, 4 and now 3.

* Notebooks were not as easy to follow. Maybe put more comments on what was expected and describe the datasets a little more.

* There are typos here and there, for instance "The pervious video referred to a colab environment you can practice one. "-> previous.

The file at https://github.com/tensorflow/datasets/blob/master/docs/datasets.md NOT FOUND

교육 기관: Pratik M

Jul 05, 2020

Very limited practice examples for learners. Also the example are very simple. The course should have been made much detailed and much real example problems. For instance, in the Week 4, topic 'Text Generation', generating a Shakespeare poem seemed to be a very silly example. The quality of Coursera Courses are becoming very poor.

교육 기관: Aladdin P

Aug 05, 2020

The material was better in this course than the previous ones, but still lacking depth in my opinion. Also, no graded assignments?? So the focus is then only on the quizzes, and they are not even well done. From week to week the same questions are repeated and the quizzes don't even include code: How is this teaching code?

교육 기관: DAVID R M

Oct 04, 2020

This course was quite sloppily presented and superficial overall. There were a couple of longstanding errors that have never been fixed (see the lengthy discussions in forums). One thing that annoyed me was that the important concept of stop-words was not discussed at all, yet it was required for the first assignment.

교육 기관: Tal F

Aug 13, 2020

All assignments were optional - probably because of all the problems with the scoring system for the previous course. Quizzes often asked things about the dataset we used (eg IMDB) rather than testing that we were learning concepts. Very little meat to the course - mostly links to other resources.

교육 기관: Hartger

Sep 29, 2020

Overall the video material is fine. The assignments however are very unclear and contain bugs. The grader's test don't match the instructions. It's very frustrating that the assignments clearly haven't been given the same attention the rest of the course has been.

교육 기관: Prosenjit D

Jan 16, 2020

This course is a far cry from Andrew Ng's deep learning specialization and refers to Sequence Models from that specialization at the drop of a hat. In short, no use doing this one, unless you have done sequence models (course 5) of deep learning specialization.

교육 기관: Dominik B

Jun 10, 2020

No grader exercises,

sample code in the lectures isn't always updated and gives errors,

everything is a bit chaotic (eg order of sample code, sample code description, introduction to the topic is random; some random parts in the code).

교육 기관: Venkata S Y T

Apr 04, 2020

The weekly exercises are not graded and the over all content quality of this course in comparison with the previous two in the specialization seems a bit poor and doesn't provide more learning on the topic.