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Learner Reviews & Feedback for Natural Language Processing in TensorFlow by DeepLearning.AI

4.6
stars
5,343 ratings
839 reviews

About the Course

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....

Top reviews

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!!

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776 - 800 of 837 Reviews for Natural Language Processing in TensorFlow

By Miguel R

Oct 25, 2020

Feels there where too many concepts not well covered

By Apoorv G

Jul 17, 2020

Short Videos are annoying. Overall content is good.

By Swetha S

May 10, 2020

No graded assignments. No conceptual explanation.

By Biao W

Apr 16, 2020

Need more explanations on the RNN models itself.

By Ramil A

Apr 15, 2020

I wish there were more graded projects.

By Igors K

Nov 21, 2019

No practical exercises that one must do

By Shubham A G

Aug 31, 2019

A bit too easy and no real assignments

By Yuxuan C

Apr 12, 2020

I wish there were graded assignments.

By Ashwin H

Apr 25, 2020

Coding assignments are much needed!

By Ahmad O

Sep 14, 2020

Assignments need some improvment.

By SUMIT V

May 28, 2020

not enough programming exercises

By giuseppe d

Jul 19, 2020

Concepts explained too quiclky

By Salem S

Apr 16, 2020

Code should be explained more

By albert

Jun 20, 2020

Not challenging enough....

By Ankit G

May 17, 2020

No programming assignments

By Leon V

Jun 13, 2020

Force me to write code.

By Artem K

Oct 6, 2020

Need more practice

By Vikas C

Dec 24, 2019

Good course

By Hamzeh A

Aug 20, 2019

good

By 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.

By Mohamed A S

Apr 8, 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.

By Sebastian F

Aug 9, 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

By Andrei I

Feb 13, 2021

The course is merely a walk-through some Jupiter notebooks of Laurence. There are no proper slides with explanation of what's going on. I also don't see much activity from the course creators on the discussion forums. It is incredibly easy to complete the course without forming any deep understanding.

The weekly programming exercises are not even automatically checked for accuracy.

By Jon d

Feb 3, 2021

I am taking these courses to learn via example. (this is not theory course, it is a course on practice). The fact that there are not well thought out programming exercises makes this course much weaker than the proceeding two. The first two courses in this series are much better for this reason. This course looks unfinished. The lectures are okay, the quizzes are okay.

By Pratik M

Jul 5, 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.