Chevron Left
Back to Sequence Models

Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

4.8
stars
30,364 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

JY

Oct 29, 2018

The lectures covers lots of SOTA deep learning algorithms and the lectures are well-designed and easy to understand. The programming assignment is really good to enhance the understanding of lectures.

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!

Filter by:

226 - 250 of 3,689 Reviews for Sequence Models

By Claes P

•

Mar 8, 2018

This course challenged me. It forced me spend more time on the things you really need to understand before moving forward. Frustrating of course, but the reward is golden. It also tells me I need to learn more Keras. I was really inspired by the exercises, by all the things you actually can create by using the superpowers of deep learning.

By Alexandre C

•

Feb 22, 2018

Excellent. I am doing a research on LTSM application for process plant data and asset health prognostics and the materials I found on the web were usually a bit "dry". The course enabled me understanding the concept mechanics and keras code basics to start using on my own applications - What else I could have asked for :D ?

Cheers/Alex

By Meenakshi S R

•

Sep 9, 2024

Thoroughly enjoyed this course - I enrolled this specialization primarily for the sequence models as my interest is on this area. And this course proved yet again a good one. Just a note, I felt this course to be more technical than any of the other courses in the specialization. And aptly it is placed as the last in the progression.

By Anurag W

•

Jul 10, 2020

I had a lot of fun doing these courses and weekly programming assignments.

Mr. Andrew Ng is a great instructor, he does a great job of explaining the neural network architecture and helps create an intuition behind difficult concept, these are really helpful at the end of each week when you are practising the programming assignments.

By Siddharth B

•

Jan 11, 2019

I am grateful to Professor Andrew Ng. and the entire team of deeplearning.ai for giving me the platform to learn, practice and showcase the deep learning concepts in such an elegant and concise manner. The journey has truly been educative and enlightening and I look forward to applying the concepts and skills in my further endeavors.

By Amit P

•

Dec 31, 2018

Andrew's ability to make complex topics so easy to understand is amazing. His explanation of the 'intuition' behind complex stuff makes you really understand what is going on and why. Very happy with the course, it provided everything I needed to know to understand it in detail and implement it. Thanks Andrew for making this course.

By Senthil K B

•

Jul 29, 2020

Very useful course for me, since I am doing research in Natural Language Processing. As NLP require RNN and its variants as its implementation, this course helped in implementing my task using the Seq2Seq model. Explanation about each topic is very clear. With respect to mathematical equations, all the models are neatly explained.

By Mm

•

Sep 29, 2019

An Amazing course which Imparts lots of knowledge.

The exercises of this course are very enjoyable and seem easy while providing really cool results, but in retrospect teach advanced material in such an engaging way that it only seems easy. The credit is with the incredible teachers of the course!

Thank you Andred Ng and all the TAs

By Vladimir L

•

Jan 5, 2019

This is a great course, it gave me a good overview of how various types of data (written text, speech, images/video) are used in neural network models. The course materials smartly omit complexities behind pre-built deep learning models, and provide students with hands-on examples, which spark creativity and imagination. Thank you!

By RISHAV S

•

Jan 2, 2019

The course is great and it builds on the last 4 course of deep learning specialization. It contains many nice topics of deep learning like RNN, NLP etc. There are some nice assignments also which you can relate with the real world. The whole Deep Learning specialization is great and every topic is nicely explained by Sir Andrew Ng.

By Parab N S

•

Aug 25, 2019

Excellent Course on Sequence Models and training on how to use RNNs for practical applications. All the programming exercises were pretty fun and highly informative giving hands on experience on the use of a variety of sequence models. I would like to thank Professor Andre N.G. and his team for developing such a wonderful course.

By Gregory B

•

Apr 24, 2023

It was a great survey of machine learning techniques applied to NLP and related tasks. In particular it was a nice build-up to the Transformer architecture that made it a lot easier to understand by the time we got to it. At the end you end up with a lot of sample code you can use to start your own projects. I really enjoyed it!

By muhammad q

•

Nov 8, 2022

very helpful course if you want to become a professional in the field of deep learning. It will enhance not only your conceptual skills but also your programming skills to write code for complex deep-learning models. The sequence model will give you a deep understanding of all the concept related to voice text emojis and models.

By Rabih M

•

Nov 21, 2020

Very Interesting course, well explained even if the topics are somehow difficult at certain points. Good and interesting Labs reflecting practical cases. But the problem was in Lab "Trigger word detection" where I encounter the error of not opening the lab and I try to solve it many times using the given solution before the lab.

By Michael L

•

May 8, 2020

Great! I would really love some signal dynamics task in this course, maybe some predictor or estimator. As an engineer I am very interested in these applications. Thank you Andrew, and huge thanks to the entire team. I am sure you guys had an extremely hard time building the programming tasks, but it looks great and helps a lot!

By Satyam D

•

Mar 27, 2019

Dear Prof Andrew Ng and deeplearning.ai team, Sequence Models is yet another excellent course where I have thoroughly enjoyed learning about new and powerful concepts of Deep Learning. The course content, quizzes and programming assignments are of the very highest quality. I am deeply grateful to the entire team. Thanks a lot!

By Rahuldeb D

•

Sep 23, 2018

Really an awesome course. A bit difficult to grasp in three weeks. But, Prof. Andrew Ng has tried his best to make the content lucid. I am great full to all the faculty members for offering such an excellent course. I personally feel that if course can extended for another week then it will easier to understand the concepts.

By Navin S

•

Jul 15, 2020

Very good course to learn things about Deep learniing. I think the Andrews courses keptmy interestin the courses with the video, quizes, assignments. I wish to challenge participants further, there should be (non-gradable) exercises based on the available util functions and contents. I mean where one has todobit more work.

By Nilanka W

•

Feb 18, 2018

Awesome course. I did not know what it meant by Deeplearning at the start of the program, but now I'm confident on finding a way. Thanks prof Andrew NG and all the Instructors and team for organizing such a rich content. You probably have put a great effort. It was challenging but fully worth. And recommending to anyone !!

By Jonathan L

•

Dec 18, 2018

Great lectures on the different structures of Sequence Models for use in Natural Language Processing, Text Translation, and Audio Recognition. There is a lot of material packed into 3 weeks, but this course will help anyone familiar with Deep Learning/CNNs to take a dive into the world of NLP and audio/speech recognition.

By Harold M

•

Dec 9, 2018

This Sequence Models and RNNs course was a very challenging course in the specialization similar to that of Convolution Networks. I've learned a lot on these topics, and I will continue expanding my knowledge from here on.

Overall, this is a great and complete specialization on Deep Learning.

Thank you professor Andrew Ng.

By Miguel C N

•

Aug 25, 2021

After having completed the Deep Learning Specialization i can say it was definitly worth it! Always top notch content, i have learned so much from these courses. I would strongly recommend them to anyone who has 0 to some knowledge of AI but has interest in the area. Thank you to the staff and everyone for this course.

By Joshua C

•

May 3, 2021

Just finished the last class of the specialization. It's amazing how far we came during the 5 classes. I'm so impressed with the way it builds from first principles into high level discussions of state of the art DL. And now they have released updates to all the classes. Can't wait to see what enhancements they made,

By Himanshu S

•

Jun 7, 2019

The topics covered in this course were a bit on the advanced side. The technologies used are most frequently used in the area of NLP. The course helps understand the basic concepts of NLP like word vectors and embedding, at the same time explains the very complex concepts like LSTM, GRUs and Attention models very well.

By Mark N

•

Apr 1, 2022

This was an excellent course to learn about sequence models. We were able to not only examine standard RNN structufre, but GRUs, LSTMs, and Dr. Ng included the most recent innovation in the field by adding in study of Transformes. I would highly recommend this course. I intend to pursue more studies in these topics.