Jul 01, 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.
Mar 14, 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!
por Shabie I•
Feb 18, 2018
Leave it up to Mr. Andrew Ng to explain complex concepts in a very much intuitive manner. The guy is a world apart when it comes to explaining complex concepts. No other MOOC even comes close. Absolutely highly recommended.
The only negative part about this course is that it ends. You don't want it to end.
por Pavel K•
Feb 05, 2019
This course offers a great introduction to the models: RNN, GRU and LSTM.
In addition, it illustrates the power of "Word Embedding" and "Attention Model".
The programming assignments are interesting, provide deeper understanding of the models, and show how simple it is to implement these models in Keras.
por Angad P S•
Feb 17, 2018
Andrew Ng knows how to make people understand the problem, architect a solution and then map it to data. He does it very well. I am going to repeat his course again as I still believe there is something that I have missed and I need to follow him thoroughly. I want to understand and process like him.
por Xiang J•
Nov 10, 2019
overall it is another great course, clear explain on the RNN, LSTM, GRU, etc. really like the assignment to implement RNN from scratch. assignments related to Keras needs "googling" outside resources, and there is still some keras homework to be done in order to fully understand the assignment code.
por Jampana b•
Feb 14, 2018
Thank you very much instructors. I learnt both fundamentals of deep learning and application of them in simple and efficient way. I have been long and fruitful journey with Andrew Ng. I learnt sound mathematics required for deep learning, tensorflow software, applications of sequence and RNN models.
por TANVEER M•
Aug 25, 2019
I have always found difficult how RNN and LSTM works as theretically I was not getting a clear picture how it was working .The programming assignments helped clear my doubts and I got a clear understanding to a lot of extent how this mechanism is working and how it is useful in speech synthesis.
por Andrei N•
Sep 21, 2019
The content, examples, assignments, and quizzes are thoroughly developed. All the courses of the specialization share the same notation and lead a student from basic concepts to complex ones helping to develop an intuition on each step. The best course on topic of Deep Learning one could find.
por Nilesh K S•
Dec 05, 2018
It was a great experience to learn from Andrew NG and it helped a lot to me personally and professionally. I have gained so much confidence after completing these set of 5 courses and looking forward to build some cool projects on my own using the concepts that i have learned in past 5 months.
por Mihir T•
Sep 23, 2018
A great course on latest technology used in NLP. The course is well structured and provides an in-depth knowledge on sequence models. This course is a all-in-one package for starting your career in NLP. Mr. Andrew is a great teacher, and explains everything in a very simple yet effective way.
por Wesley H•
Aug 08, 2019
Great finish to the specialisation. I have learned a lot of the core details of how to proceed with my own Deep Learning projects. My one piece of feedback would be for an intermediary step, that requires more of the programming myself, as a lot of the intricate coding has already been done.
por Isaac S J C•
Nov 06, 2018
Great appreciation to Dr. Andrew Ng. The course has been incredibly well taught. Thank you so much for your enlightening lectures. I very much enjoyed the course, and I think it is very well structured and organized. The forum was very helpful when I got stuck in the programming exercises.
por Anujay S•
Sep 30, 2019
I am amazed with the learning experience of Seq2Seq Modules created by deeplearning.ai team! Loved the way it's taught by Andrew Ng and the hands on experience helped the mentee very well. Keep building such courses, would like to contribute more in this space as in research or products.
por Kyle L•
Feb 15, 2018
Insightful detail on model architectures and how they influence (and are influenced by) data generation for sequence-based applications. For those that have grasped the theory behind DNNs and are interested in applying ML to language and text, I highly recommend checking out this course!
por Kumar S•
Aug 30, 2019
This course was really awsome,learning has been fun in all the 4 courses, the number of new things learnt in this course was remarkable.Even the mot complicated things were taught in such a way that it never seemed tough.Doing assignments really helped to make concepts even more clear.
Feb 17, 2018
Fantastic course! Presents both the theory and practical uses in a straightforward manner that is easy to grasp. Programming assignments are a mix of NumPy and Keras API, with the former being more illustrative of the inner workings of RNNs and the latter being more practically useful.
por Nicolas C•
Feb 17, 2018
Excellent! Amazing! Such good quality of lecture and assignments. Thank you Andrew and team for giving me such a good overview of what i can use this for. I feel as though this series dramatically lowered the barriers to entry for me to get started on any ML project i decide to. Thanks
por Aman K•
Feb 13, 2018
This was by far the Best Course and Specialization that I have done. Thank You Coursera and Thank You Sir Andrew NG . You have made me confident and able in the Field of Deep Learning. I am grateful to you Sir. I will try my best to use this knowledge as a superpower in the right way.
por Liyan X•
Jun 03, 2018
Great course with interesting exercises. One can really see the amount of effort being put into creating the assignment material, so they are at a suitable level and with a lot to take away, and the students have a good understanding of details through practice. Really appreciated.
por Jayash K•
Jul 07, 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 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
por Kevin P B•
Mar 02, 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•
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.
por 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.
por Andrew M•
Jul 09, 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 Koki 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()