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!
MK
Mar 13, 2024
Cant express how thankful I am to Andrew Ng, literally thought me from start to finish when my school didnt touch about it, learn a lot and decided to use my knowledge and apply to real world projects
By Havryliuk A
•Oct 21, 2022
An excellent course in every way. The presentation of the material, a charismatic lecturer, interesting tasks - everything was just perfect. Thank you so much for the opportunity to take this excellent course, I am eternally grateful to you and I want to take all the courses that you have released!
By 邓佳阳
•Jun 8, 2020
非常感谢老师提供的课程,原本课程实验对LSTM有相关研究需求,该课程很关键的提供了相关知识点的教学,再次感谢老师和平台!
Thank you very much for the course provided by the teacher. The original course experiment has relevant research needs for LSTM. This course provides the teaching of relevant knowledge points. Thank you again for the teacher and platform!
By Pawan S S
•Jan 8, 2021
A very good course to learn the fundamentals of Sequence models. It contain a lot of important developments of the sequence models and together with the programming assignments, it makes easier to learn. I found this course very easy to follow and understand the theories. I highly recommend this.
By 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.
By Zhiming C
•Jun 14, 2020
This course introduces the basic idea of RNN, GRU and LSTM models. They are obviously harder than the CNN models and the concepts are not so easy to understand. Thanks to the systematic introduction! Together wit the excises I can understand better the theory from the applications. It's great!
By 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.
By Nilesh K S
•Dec 5, 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.
By 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.
By Wesley H
•Aug 8, 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.
By Toshi T
•Jun 8, 2022
Great selection of topics, clear explanations from Dr. Ng, and coding exercises to allow the understanding of the topics. Perhaps I would have liked to see some Time series analysis in the Sequential Networks parts, but even though, it was a great course. Thank you Dr. Ng and all your team!
By Srikar C
•May 7, 2020
The course content is very good but the mistakes in the videos are being mentioned after the video. This is making us get confused a bit. It would be good if those errors are mentioned before the video itself so that we can look into that before watching the video and get prepared for that.
By Wingyan C
•Mar 1, 2022
Excellent teaching, materials, and organization! It's great to include state-of-the-art technologies like Transformer and LSTM. I would recommend also teaching some practical skills (like TensorFlow) that students can apply directly in practical programming (beyond the course assignments).
By Isaac S J C
•Nov 5, 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.
By Mikhail K
•Jul 22, 2022
It is a great course, and the same applies to the whole Deep Learning Specialisation. It is very nice to see that many people all around the world can relatively easily get access to these learning materials as well as to the problem exercises. Thank you for making it widely available !
By 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.
By 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!
By Cezary B
•Jun 19, 2022
Great course, well explained. Sometimes the course material gets a bit too general but this is done when the details would be unbearable to cover. The overview of all the machine learning conepts is an amazing start for purusing anything deep learning related in my novice point of view.
By AS A
•Apr 7, 2021
I like the course. It's beneficial and clear. Also, the concept is clear.
for more improvement
I would suggest that for jupyter implementation :
I hope you put 2 versions of the code
thus, the student can have a choice to work on a famous frame
1- using Tensorflow (TF)
2- using PyTorch
By 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.
By Lee F
•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.
By 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
By Manmohan K
•Jul 2, 2020
No better introductory material. I suggest doing NLP specialization by deeplearning.ai after this though I have still not tried it out myself yet but hoping to do it some time. Thank you Andrew! I got emotional in your last video of the course. You are such an example for educators <3
By 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.
By Jeremy S
•Sep 10, 2023
Amazing course and specialization. I feel so fortunate to have found Andrew Ng's courses. His teaching is so clear and conveys the intuition so well. To Andrew, thank you so much for for continuing to provide this service even as you have achieved such a high status in this field.
By Laks P
•Apr 30, 2022
1) Course over all is good.
2) I had a slight difficulty understanding the WW4 section, Transformer concept "guts" even though I happed to score 100 on the course. Possibly with some more practice, I should be able to understnd Transformer, multi-head attention model concepts better.