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!
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.
By anand k
•Apr 2, 2020
the programing assignment ins WEEK 1 was a bit ambiguous in nature. helped me improve my debugging skills.
Also a huge thank you to MENTOR Mr. GEOFF for the instant support to all my queries. His way of providing HINTS lead me to finally complete the course. a BIG thank you to him.
By Manhal R
•Jun 21, 2020
More easier to understand than the ConvNets course!
Week 1 and 2 took me a little time to get through. Week 3 is easy.
For better understanding, don't forget to download the notebooks and practice on your own local Jupyter notebook while using the assignment notebook as a reference.
By Jayash K
•Jul 6, 2018
This is a great course. It provides a good introduction to RNNs and how they are used in sequence modeling. Introduction to GRU, LSTMs, BiRNNs, attention model is great way to learn these in depth. The exercises are designed to make you familiar with the internals of these layers.
By Sandeep M
•Aug 6, 2022
I can't thank Andrew Sir and Coursera enough for enabling me with this wealth of knowledge in NLP. With this I can dive deeper into NLP and look at a career change as well into this area. The course has immensly boosted not only my knowledge but also my confidence. Much obliged.
By Dong Z
•Aug 18, 2020
At the beginning this is very counter-intuitive. But later on when I am on the final assignment, I finally realized that we are not focusing on gradient descent, but architecture building and training set assembling! When everything start to make sense, it is really intriguing.
By Kyung-Hoon K
•Apr 29, 2020
This course made me have great understanding around the Sequence Models such as GRU, LSTM, Attention, etc. I had a lot of fun while completing programming exercises such as Trigger word detection. As always, it was one of the best class ever. Thanks Professor Andrew Ng and all-!
By Vladimir B
•Mar 14, 2018
Very good course. In quite short time you get understanding of a lot of principles and intuitions. The pace is good, explanations are consistent and clear, top-down approach from generic to specific, from simple to complex, very good instructional videos and interesting projects
By k. p b
•Mar 2, 2018
Remarkably lucid exposition of complex learning architectures with directly applicable programming exercises. Highest recommendation. Thanks to the deep learning.ai staff for putting this entire specialization together and sharing their abundantly clear mastery of the subjects.
By Tun C
•Aug 28, 2018
Some of the lectures were not quite up to par with professor Ng's standard. Some of the programming assignments were hard to follow and missing some details. Nevertheless, I came away with good understanding of sequence models and RNN. I can't thank enough. 5 stars from me.
By Julia C
•May 27, 2019
This is very logical and especially the addition of probability between the words to improve predictions. It will be interesting to compare language , which language is easier to predict and why and study backward- how human creates them. We might learn something unexpected.
By Ayush G
•Jun 27, 2020
The lectures were super informative. It's almost unreal how easily he explains such difficult concepts, such they look a child's play. The coding assignments are incredibly informative and super interesting. I am very thankful for this specialization that it taught me so much
By andrew m
•Jul 9, 2019
Before starting the course, I wanted to have a strong knowledge of the basics of Natural Language Processing as I wanted to specialize in this domain. I am thoroughly satisfied at the end of this course. This course has given me the confidence to dive deeper into this domain.
By kk s
•Mar 30, 2019
Course of lectures are excellent, but please fix the following problem
week 1 Programming Assignments
Improvise a Jazz Solo with an LSTM Network - v3
Dimensionality in djmodel()
https://www.coursera.org/learn/nlp-sequence-models/discussions/weeks/1/threads/NAoSHgf0Eei8aw6tWi-efA
By Anurag S
•Jun 1, 2020
I'll remain forever indebted to Andrew and his team for preparing this rigorous course. I can imagine the effort put in designing video lectures, going through research papers, crafting out these well-knit coding exercises. He has democratized AI and education in true sense.
By Lucas S
•Jan 21, 2019
I appreciate all the hard work and effort Andrew and his team puts in all his material.
I had hard time with most of Keras homework’s, I think it's hard to get the overall logic of a framework without an extensive explanation.
Besides that, the topics discussed are amazing.
By Haider k
•Dec 8, 2019
A great introduction to Recurrent Neural Network models with lots of examples (text generation, music generation, sentiment analysis, word embedding, speech recognition, attention-based machine translations etc.). Thanks a lot to Andrew and the team for this awesome course.
By FS
•Sep 12, 2018
Andrew, again explained complicated structures very clearly. The first week might be a bit overwhelming and you might get lost with huge information overflow, but trust me, in week2 and week3 you will see how the dots are connected. Thank you Andrew for this amazing course.
By ABHINAV G
•Feb 15, 2020
Thanks for making this course! I have been through all the courses in this specialization, and they are really excellent! Andrew has a great way of explaining things simply. It was easier for me to look at a couple of research papers after having gone through the lectures.
By Mohamad K
•Feb 26, 2019
Prof Andrew such a great person. He teaching from the heart where 99 % of Prof not doing it today.
He summarized Deep learning+ Computer vision+ NLP in easy way. I am thankful for Coursera and Prof Andrew. I strongly recommend this course and all his courses to everybody .
By Akanksha D
•Sep 26, 2018
Awesome. But the programming assignments need to be less erroneous and lectures and assignments could contain more technical and mathematical details to build the foundations. The programming assignments could be designed to allow the students to do more that spoonfeeding.
By Alouini M Y
•Feb 20, 2018
This was for me the best course on the deeplearning.ai series since I am a complete novice regarding sequence models. Nonetheless, I have managed to learn a lot and the material was very good (with often state of the art techniques). The assignments were excellent as well!
By Aleksa G
•Jan 20, 2019
I really liked this last course as I did not have much experience with NLP and with audio in general, as I did have with computer vision and image processing. The keyword detection model is really cool! After this specialization I am starting to build my own ML projects!
By Raivis J
•Mar 18, 2019
This is the hardest course in the specialisation, and may take some extra effort. For practical assignments I recommend getting familiar with Keras syntax and workflow, as here there is little hand-holding here,. the focus is on actual model architecture and algorithms.
By Zein S
•Feb 15, 2018
This is not a good course, and even not a good tutor.. It is a great course and Andrew is really incredible tutor... I like this course so much and got tons of benefits...
I am so happy to take this course..
PS: You can add this review to the sentiment analysis data set
By Guilherme
•Jun 10, 2018
I really enjoyed the models presented in the course, as well as the accompanying exercises; I think Andrew and the team did a good job at giving intuition about the problems and coupling that with enough hands exercises to give better understanding of the implemtations