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Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

4.8
stars
26,479 ratings
3,123 reviews

About the Course

In the fifth course of the Deep Learning Specialization, you will become familiar with NLP models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language understanding, and more that have become possible with the evolution of sequence algorithms thanks to deep learning. By the end, you will be able to build and train Recurrent Neural Networks 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. DeepLearning.AI is proud to partner with NVIDIA Deep Learning Institute (DLI) to provide a programming assignment on Machine Translation with Deep Learning. Get an opportunity to build a deep learning project with leading-edge techniques using industry-relevant use cases. The Deep Learning Specialization is our 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 gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

Top reviews

AM
Jun 30, 2019

The course is very good and has taught me the all the important concepts required to build a sequence model. The assignments are also very neatly and precisely designed for the real world application.

WK
Mar 13, 2018

I was really happy because I could learn deep learning from Andrew Ng.\n\nThe lectures were fantastic and amazing.\n\nI was able to catch really important concepts of sequence models.\n\nThanks a lot!

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2951 - 2975 of 3,095 Reviews for Sequence Models

By Sebastian S

Mar 14, 2019

The ideas presented here were clear, however I found the programming assignments non-intuitive and not practical. I spent on them way more time than I wish i had.

By Fernando A G

Jul 27, 2018

I enjoyed all the courses, from my personal point of view this course was not that fun as the other courses. Except for the trigger assignment it was awesome!

By Zhao H

Jul 6, 2018

Too much was given in external python code for the first week's assignment (that should be learnt by us): not a good thing for us to gain a good understanding

By Matias A

Aug 11, 2020

Worst course of the specialization, content is interesting and Andrew keeps explaining really well but programming assignments are clearly of a lower quality

By Max W

Sep 7, 2018

The course is great but the tasks in Keras are too complex without background knowledge. Therefore, a reasonable introduction in Keras would be desirable.

By Eymard P

Jul 31, 2018

Far less detailed than the other ones. The programming assignements are less interesting too, as a great part of the work consist of reading documentation

By Reetu H

Dec 23, 2019

There were lot of bugs in the assignments taking up lot of time to fix. The course was okay, I liked the other courses in the specialization more.

By Kaupo V

May 7, 2018

The Keras programming exercises are quite weak. Please re-think how to teach them more systematically. Currently it is quite a lot of hit and miss.

By Assa E

Feb 10, 2021

That was much harder than the previous courses of the specialization. However it felt like the videos are more hasty and less understoodable

By Leandro A

Mar 18, 2018

There was a bug in a programming assignment notebook that took too much time to notice that i was doing ok but the expected ouptut was wrong

By David H P

Apr 2, 2018

The programming assignments required some extra effort to understand Keras which I thought may need an introduction video like tensorflow.

By Iván V P

Feb 18, 2018

Several grader issues, only 3 weeks of work, and a lot of errors in the solutions... In addition, less content than in the other courses...

By Rishabh G

Sep 19, 2020

The earlier courses were easy to understand, however, this was way too difficult. Andrew Ng did not make this easy like the other courses.

By H Y

Aug 24, 2018

Compared with previous courses, this one seems to be rushed. The focus on applications seems to be much higher than the theoretic side.

By Yash R S

May 9, 2018

Not as great as the other courses in the specialisation. The assignments can be a little off putting, but lectures are top class again.

By Roberto S

May 12, 2020

Week 1 took double time to be completed. Times proposed for the assingnement are underestimated.

Please readjust the assingement time.

By Ankit S

Jul 17, 2018

Assignments are not up t the mark.. Expected to have high vocabulary size word embedding assignment, Machine Translation assignments

By Nachiketa M

Feb 16, 2018

This course was good but in comparison to the other courses in the deeplearning course series, this course lacked adequate depth.

By 1140325971

Jan 23, 2020

The course is a good course because the lecture Ng.W ,but the exercises is not easy for our beginers for such tools like kears.

By Seng P T P P

Nov 8, 2019

The programming assignments in this course are difficult to implement. The detail descriptions are needed inside the notebooks.

By Thomas N

Mar 9, 2018

Good subject, but a lot of the course material (like lecture slides and problem sets) was either unavailable or out of date.

By Vinjosh V

May 11, 2020

The videos are great - however it would be useful to provide some help on how to implement the concepts programatically.

By Søren M

Feb 16, 2018

Not as good as the previous courses in the series, and some of the assignments where broken, and super hard to debug.

By Laurent B

Jan 12, 2021

Only on NLP applications, it would have been great to apply GRU or LSTM on numerical data like finance for example.

By Devansh K

Sep 20, 2020

The content covered is interesting, but I feel like the explanations are not as intuitive as the previous 4 courses