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Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

4.8
stars
30,203 ratings

About the Course

In the fifth course of the Deep Learning Specialization, you will become familiar with sequence models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language processing (NLP), and more. By the end, you will be able to build and train Recurrent Neural Networks (RNNs) and commonly-used variants such as GRUs and LSTMs; apply RNNs to Character-level Language Modeling; gain experience with natural language processing and Word Embeddings; and use HuggingFace tokenizers and transformer models to solve different NLP tasks such as NER and Question Answering. The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career....

Top reviews

WK

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I was really happy because I could learn deep learning from Andrew Ng.

The lectures were fantastic and amazing.

I was able to catch really important concepts of sequence models.

Thanks a lot!

GS

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So many possibilities will be presented in front of you after this course. The only limit is the boundary of my imagination and creativity, that is how I feel now upon the completion of this course.

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3551 - 3575 of 3,671 Reviews for Sequence Models

By Iván G

Mar 13, 2019

Not as good as structured in explanation nor in programming assigments as the last ones.

By mohsin j

Jun 7, 2018

This is only good enough, not good course. All previous ones were 5 stars, definitely!

By jinwei z

Feb 1, 2022

the lab and programming is not as intuitive as the first two course in the specilism.

By Thomas P

Apr 9, 2020

Overall a great class. I had some trouble understanding the programming assignments.

By Manuel M

Aug 13, 2023

The transformer content was very light and not clear relative to the other content.

By Archana A

Oct 7, 2019

This felt the the least prepared and organized course of the series, unfortunately.

By Ankit A

Jul 17, 2022

give projects that we can build from ground up without your inbuilt function.

By Sébastien C

Aug 18, 2020

Good theoretical overview - project just require you to fill in lines of code

By BORIS M

Oct 1, 2022

Lectures on week4 are not complete as confirmed by mentor in the community

By Hieu N

Jan 28, 2024

This course is the hardest in the Specialization but is also the shortest.

By Zhiyu Z

Aug 28, 2022

Week 4 labs need to be better, the layers under the classes were confusing

By Samit H

Aug 18, 2020

I found this course boring and also too many assignments in a single week.

By Tushar B

Jun 12, 2018

Issues with assignments. Took more than 4 hours to figure out the problem.

By Saeif A

Jan 3, 2020

This was the least clear course among the others. The others were great!

By Nikolai K

Jun 18, 2023

The last week of this course was designed in a hurry, quick and dirty.

By Ragav S

Sep 18, 2019

Would like to learn a bit on how back-prop works when using attention.

By Gaetan J d B

Jun 17, 2019

fairly more complex and deeper as previous courses. Nice ex. however.

By Yun W

Apr 6, 2019

I feel this course is not as carefully designed as previous courses

By mayukh m

Apr 16, 2020

Trigger word detection - v1.ipynb bug is annoying. Course is good.

By yuichi k

Jul 27, 2020

ほぼ英語、プログラムの課題の問題を解決するのが非常に大変だった。bugも多いのでこなすのは苦労した。ビデオは相変わらず素晴らしい

By prateek s

Apr 22, 2020

Good Course but lectures and assignments could have been better.

By bernd e

Mar 10, 2018

Should be five weeks instead of three. Dive deeper into Details

By ashok j

Jan 13, 2024

Need to know a lot about tensorflow to complete some courses.

By Rohan L

Nov 15, 2021

lecture videos were good but in assignments let us code more.

By Ar-Em J L

Oct 30, 2019

One of the weaker courses in the specialization. Felt rushed.