Finally, after 6 months achieved desired goal in Deep Learning Specialization.

Thanks to #andrewng #coursera team for motivation and opportunity. It was not possible but due to #andrewng motivational words and explained deep knowledge in simple words. I can't express my feeling in words. Thanks again

Best wishes for Andrew Ng and Coursera Team

Excellent as always. This subjectcould easily take more weeks or even months to understand, but Andrew explains complicated concepts in very easy terms. Though sometimes it seems a bit esoteric and magical, due to how easy he makes it sound, it's a great start point to begin to investigate, read and implement the most important algorithms.

This course challenged me. It forced me spend more time on the things you really need to understand before moving forward. Frustrating of course, but the reward is golden. It also tells me I need to learn more Keras. I was really inspired by the exercises, by all the things you actually can create by using the superpowers of deep learning.

Excellent. I am doing a research on LTSM application for process plant data and asset health prognostics and the materials I found on the web were usually a bit "dry". The course enabled me understanding the concept mechanics and keras code basics to start using on my own applications - What else I could have asked for :D ?

Cheers/Alex

I had a lot of fun doing these courses and weekly programming assignments.

Mr. Andrew Ng is a great instructor, he does a great job of explaining the neural network architecture and helps create an intuition behind difficult concept, these are really helpful at the end of each week when you are practising the programming assignments.

I am grateful to Professor Andrew Ng. and the entire team of deeplearning.ai for giving me the platform to learn, practice and showcase the deep learning concepts in such an elegant and concise manner. The journey has truly been educative and enlightening and I look forward to applying the concepts and skills in my further endeavors.

Andrew's ability to make complex topics so easy to understand is amazing. His explanation of the 'intuition' behind complex stuff makes you really understand what is going on and why. Very happy with the course, it provided everything I needed to know to understand it in detail and implement it. Thanks Andrew for making this course.

Very useful course for me, since I am doing research in Natural Language Processing. As NLP require RNN and its variants as its implementation, this course helped in implementing my task using the Seq2Seq model. Explanation about each topic is very clear. With respect to mathematical equations, all the models are neatly explained.

An Amazing course which Imparts lots of knowledge.

The exercises of this course are very enjoyable and seem easy while providing really cool results, but in retrospect teach advanced material in such an engaging way that it only seems easy. The credit is with the incredible teachers of the course!

Thank you Andred Ng and all the TAs

This is a great course, it gave me a good overview of how various types of data (written text, speech, images/video) are used in neural network models. The course materials smartly omit complexities behind pre-built deep learning models, and provide students with hands-on examples, which spark creativity and imagination. Thank you!

The course is great and it builds on the last 4 course of deep learning specialization. It contains many nice topics of deep learning like RNN, NLP etc. There are some nice assignments also which you can relate with the real world. The whole Deep Learning specialization is great and every topic is nicely explained by Sir Andrew Ng.

Excellent Course on Sequence Models and training on how to use RNNs for practical applications. All the programming exercises were pretty fun and highly informative giving hands on experience on the use of a variety of sequence models. I would like to thank Professor Andre N.G. and his team for developing such a wonderful course.

Very Interesting course, well explained even if the topics are somehow difficult at certain points. Good and interesting Labs reflecting practical cases. But the problem was in Lab "Trigger word detection" where I encounter the error of not opening the lab and I try to solve it many times using the given solution before the lab.

Great! I would really love some signal dynamics task in this course, maybe some predictor or estimator. As an engineer I am very interested in these applications. Thank you Andrew, and huge thanks to the entire team. I am sure you guys had an extremely hard time building the programming tasks, but it looks great and helps a lot!

Dear Prof Andrew Ng and deeplearning.ai team, Sequence Models is yet another excellent course where I have thoroughly enjoyed learning about new and powerful concepts of Deep Learning. The course content, quizzes and programming assignments are of the very highest quality. I am deeply grateful to the entire team. Thanks a lot!

Really an awesome course. A bit difficult to grasp in three weeks. But, Prof. Andrew Ng has tried his best to make the content lucid. I am great full to all the faculty members for offering such an excellent course. I personally feel that if course can extended for another week then it will easier to understand the concepts.

Very good course to learn things about Deep learniing. I think the Andrews courses keptmy interestin the courses with the video, quizes, assignments. I wish to challenge participants further, there should be (non-gradable) exercises based on the available util functions and contents. I mean where one has todobit more work.

Awesome course. I did not know what it meant by Deeplearning at the start of the program, but now I'm confident on finding a way. Thanks prof Andrew NG and all the Instructors and team for organizing such a rich content. You probably have put a great effort. It was challenging but fully worth. And recommending to anyone !!

Great lectures on the different structures of Sequence Models for use in Natural Language Processing, Text Translation, and Audio Recognition. There is a lot of material packed into 3 weeks, but this course will help anyone familiar with Deep Learning/CNNs to take a dive into the world of NLP and audio/speech recognition.

This Sequence Models and RNNs course was a very challenging course in the specialization similar to that of Convolution Networks. I've learned a lot on these topics, and I will continue expanding my knowledge from here on.

Overall, this is a great and complete specialization on Deep Learning.

Thank you professor Andrew Ng.

The topics covered in this course were a bit on the advanced side. The technologies used are most frequently used in the area of NLP. The course helps understand the basic concepts of NLP like word vectors and embedding, at the same time explains the very complex concepts like LSTM, GRUs and Attention models very well.

This course is perfect to learn deep insights of natural language processing, word2vec, speech recognition, trigger word detection and sentiment analysis among others. This course not only trains in using open-source libraries, but also trains to learn how to implement these life-changing techniques all by ourselves.

Deep learning specialization is one of the best courses I've ever done. When I used to work on Computervision prior to this course, I used to stumble a lot conceptually and in implementation. This specialization gave me a pragmatic insight into the DL. Can't thank coursera, deeplearning.ai and instructors anymore. :)

What an awesome course it was? I have completed my Deep Learning Specialization. It was a about three month journey with Coursera and Andrew Ng. I really miss Andrew. I suppose, I will see you, Andrew Ng, in another Machine Learning Specialization on Coursera course. Till than, I am waiting what will come from you.

This course gives an in depth explanation and intuition of RNNs used for learning tasks involving Sequences.

The time required to complete programming assignments takes usually more than an hour to complete than the specified time.

Rest it was a very exciting journey to learn deep learning along with Andrew Ng sir!