30 de jun de 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.
29 de out de 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.
por Manhal R•
21 de jun de 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.
por Jayash K•
6 de jul de 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.
por Dong Z•
18 de ago de 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.
por Kyung-Hoon K•
29 de abr de 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-!
por Vladimir B•
14 de mar de 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
por Kevin B•
2 de mar de 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.
por Tun C•
28 de ago de 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.
por Julia C•
27 de mai de 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.
por Ayush G•
27 de jun de 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
por Andrew M•
9 de jul de 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.
por kk s•
30 de mar de 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()
por Anurag S•
1 de jun de 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.
por Lucas S•
21 de jan de 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.
por Haider A K•
8 de dez de 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.
por chloe s•
12 de set de 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.
por ABHINAV G•
15 de fev de 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.
por Mohamad K•
26 de fev de 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 .
por Akanksha D•
26 de set de 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.
por Alouini M Y•
20 de fev de 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!
por Aleksa G•
20 de jan de 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!
por Raivis J•
18 de mar de 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.
por Zein S•
15 de fev de 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
10 de jun de 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
por Juan V M•
30 de jun de 2018
Greatly explained. A lot of things explained in detail in just no that-much videos. Totally worth-it the specialisation!! Went from zero knowledge to know a lot of things about how it really works. Learned python (including keras and tensorflow) along the way as well.
por David W•
18 de fev de 2018
Thanks for an enlightening course about sequences and how to apply machine learning concepts. This course has brought new light to how to solve some difficult sequencing tasks in my day to day work and I plan on looking for future courses from Andrew Ng in the future!