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Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

4.8
stars
30,441 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

Mar 13, 2018

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!

MK

Mar 13, 2024

Cant express how thankful I am to Andrew Ng, literally thought me from start to finish when my school didnt touch about it, learn a lot and decided to use my knowledge and apply to real world projects

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3576 - 3600 of 3,705 Reviews for Sequence Models

By Joao C M

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Sep 29, 2023

Very good content but several Python exercises were far-fetched for the novice Python programmer

By Andrei M

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Jun 18, 2018

The content is super interesting, but the assignments are more of the same 'fill in the blank'.

By Lars O A

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May 29, 2018

Put to much focus into getting the Keras code to work instead of truly learning the algorithms.

By NAGARAJ R

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Jan 23, 2019

I found this very hard to follow along. The concepts were too heavy and needs a slower pace.

By Anmol D

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Mar 21, 2021

Theory explained in a better way, but practicals could have been more involved and better.

By Sidharth S

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Dec 23, 2018

Really Nice course. Could have been more fun if Keras and it's functioning had more focus.

By Uttam R

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Mar 26, 2018

Course is got but grader compilations are horrible spent more time on them than the course

By Iván G

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Mar 13, 2019

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

By mohsin j

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Jun 7, 2018

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

By jinwei z

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Feb 1, 2022

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

By Thomas P

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Apr 9, 2020

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

By Manuel M

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Aug 13, 2023

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

By Archana A

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Oct 7, 2019

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

By Ankit A

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Jul 17, 2022

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

By Sébastien C

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Aug 18, 2020

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

By BORIS M

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Oct 1, 2022

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

By Hieu N

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Jan 28, 2024

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

By Zhiyu Z

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Aug 28, 2022

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

By Samit H

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Aug 18, 2020

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

By Tushar B

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Jun 12, 2018

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

By Saeif A

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Jan 3, 2020

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

By Nikolai K

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Jun 18, 2023

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

By Ragav S

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Sep 18, 2019

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

By Gaetan J d B

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Jun 17, 2019

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

By Yun W

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Apr 6, 2019

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