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 Xiang J•
9 de nov de 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•
14 de fev de 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.
8 de jun de 2020
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!
por Pawan S S•
8 de jan de 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.
por TANVEER M•
25 de ago de 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 Zhiming C•
14 de jun de 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!
por Andrei N•
21 de set de 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•
5 de dez de 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•
23 de set de 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•
8 de ago de 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 Toshi T•
8 de jun de 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!
por Challa S•
7 de mai de 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.
por Wingyan C•
1 de mar de 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).
por Isaac S J C•
5 de nov de 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 Mikhail K•
22 de jul de 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 !
por Anujay S•
30 de set de 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•
15 de fev de 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 Cezary B•
19 de jun de 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.
por AS A•
7 de abr de 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
por Kumar S•
30 de ago de 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.
por Lee F•
17 de fev de 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•
17 de fev de 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 Manmohan K•
2 de jul de 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
por Aman K•
13 de fev de 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 Laks P•
30 de abr de 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.