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

4.6
stars
6,491 ratings

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 Developer 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 Developer 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

FQ

Oct 26, 2023

I already had some theoretical background from the Deep Learning Specialization from Andrew Ng, but with this course, I feel much more confident about building real-world applications with TensorFlow.

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!

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626 - 650 of 1,002 Reviews for Natural Language Processing in TensorFlow

By Dini P U

•

Nov 2, 2023

good

By Nur T R

•

Jul 24, 2021

Nice

By M. s

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Jul 24, 2021

good

By Suci A S

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Jun 19, 2021

good

By Alivia Z

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Apr 25, 2021

good

By Ahmad H N

•

Mar 31, 2021

Good

By Indah D S

•

Mar 28, 2021

cool

By Johnnie W

•

Oct 7, 2020

nice

By Edgar D J E

•

Sep 11, 2020

Good

By RAGHUVEER S D

•

Jul 25, 2020

good

By Estrella P

•

Jul 16, 2020

nice

By Yu-Chen L

•

Jun 26, 2020

Good

By Hyungjune L

•

Jan 21, 2020

good

By Amini D P S

•

Apr 8, 2022

wow

By Roberto

•

Apr 21, 2021

ty

By Mohamed M

•

Sep 30, 2020

<3

By KEERTHI S

•

Aug 28, 2020

Ok

By Ming G

•

Sep 11, 2019

GJ

By Rahmalia N

•

May 1, 2024

-

By 김윤성

•

Aug 13, 2021

.

By Ajay T

•

Dec 18, 2019

s

By Kirt U

•

Sep 12, 2020

Course material: 5 stars (although it could be more rigorous, this is part of an into to dln with Keras). The course dropped the requirement for code submission which I thought was a bad idea - code submission should be required. Tools: 3 stars - these are standard tools but honestly the tools are still pretty bad (by which I mean you have to use them a bit to get used to them - I have always objected to this is software development and in code I wrote conventional was not relied upon as a requirement).

By James P

•

Aug 3, 2020

The lectures were great. And I liked that there were still examples for us to work through like the previous courses in the specialization. That being said there were frequently concepts that seemed to be introduced in the examples that were never before mentioned and thus seemed out of place as they were not necessary to complete the assignment. It might be helpful to include short introductory statements to some of these so that we can better learn when/why some of these concepts are used.

By João A J d S

•

Aug 3, 2019

I think I might say this for every course of this specialisation:

Great content all around!

It has some great colab examples explaining how to put these models into action on TensorFlow, which I'm know I'm going to revisit time and again.

There's only one thing that I think it might not be quite so good: the evaluation of the course. There isn't one, apart from the quizes. A bit more evaluation steps, as per in Andrew's Deep Learning Specialisation, would require more commitment from students.

By Edgar C O

•

Jul 20, 2020

This a great course on it own, it contains the fundamentals for natural language processing, from the encodings, embeddings and all the process involved before you can actually use the sequences into recurrent neural networks. I was hoping to do more exercises and with a higher difficulty than the ones defined here that are more focussed on the fundamentals. I mean these were good, the pre-processing is always good but I would like more design/program more models.