30 июня 2019 г.
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 окт. 2018 г.
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.
автор: Josh C•
3 мая 2021 г.
Just finished the last class of the specialization. It's amazing how far we came during the 5 classes. I'm so impressed with the way it builds from first principles into high level discussions of state of the art DL. And now they have released updates to all the classes. Can't wait to see what enhancements they made,
автор: Himanshu S•
7 июня 2019 г.
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.
автор: Mark N•
1 апр. 2022 г.
This was an excellent course to learn about sequence models. We were able to not only examine standard RNN structufre, but GRUs, LSTMs, and Dr. Ng included the most recent innovation in the field by adding in study of Transformes. I would highly recommend this course. I intend to pursue more studies in these topics.
автор: Adam F•
1 нояб. 2021 г.
I completed the entire specialization and having nothing but good things to say. Highly recommend it! Lectures are engaging, and Andrew does a fantastic job explaining some very complex topics. Programming assignments are challenging in a good way. You’ll really feel like you’ve learned a lot by the time you’re done.
автор: Uday K B•
12 дек. 2019 г.
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.
автор: Sharath G•
22 февр. 2019 г.
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. :)
автор: Ahammad U•
11 нояб. 2020 г.
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.
автор: Sanket D•
1 июня 2020 г.
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!
автор: Anne G•
13 сент. 2019 г.
I have thoroughly enjoyed the course from start to end! Each course is well organized, the teacher taught really well, and the programming assignments are very rich with easy to follow guidance, and lots of good libraries / functions that we can leverage / learn from. Thank you very much! Have a wonderful day!
автор: jaylen w•
8 нояб. 2018 г.
Finally I finished the whole series of Deep Learning AI, through which I gained a lot of intuition of deep learning algorithms and its implementation. It's great course to get into this new era especially with a excellent teacher like Andrew who really illustrates the core ideas of deep learning algorithms to me.
автор: Pavel K•
31 мар. 2018 г.
The last module is awesome as all previous ones. Thank you all guys!
Thank you guys who posted questions, thank you guys who posted answers as well. I appreciate you all. And one more special appreciation to Andrew Ng for this entire course. This course gave me a great knowledge and intuition about Deep Learning.
автор: Rajan A•
22 июня 2020 г.
I have been through wonderful journey of learning and implementing deep learning from very scratch. This course really transforms one from caterpillar to butterfly with very minimal pain of calculus and linear algebra. Thanks to Andrew and deeplearning.ai team for providing such a marvelous bundles of knowledge.
автор: sam h•
9 февр. 2018 г.
Lots and Lots of knowledge and experience in 3-weeks of class. In Machine Learning terms, this course maximizes the knowledge and experience gained with sequence models by minimizing the time required to complete the course. Lecture videos are very intuitive while assignment projects are very real-world centric.
автор: Saimur R A•
5 сент. 2020 г.
As always one of the best courses offer by coursera and it was a hell of a ride. I learned about many things like RNN,sequence model,GRU,LSTM,word triggered,word sampling,translation using deep learning algorithm . Andrew did a fantastic job and keep everything simple so that everything can be understandable.
автор: Matei I•
31 мар. 2019 г.
Really good choice of topics, including state of the art tools like attention and word embeddings. Very useful, especially for those interested in Language Processing applications. However, the videos and assignments need some more careful editing, because there are occasional mistakes, lazy explanations etc.
20 янв. 2020 г.
Very great and aspiring course, I learned lots of concepts in this course. I think It would be better If there was a capstone project for the final course of deep learning specialization. It was very great but If I had the opportunity of implementing a project from zero to 100, It would be more than great...
2 сент. 2018 г.
Great course, though not as awesome as other Ng's courses. I think creators became a bit tired closer to the last course in specialization. Anyway, fantastic courses, fantastic specialization, fantastic professor! Thank you very much!! Looking forward to new courses - maybe Reinforcement Learning, GANs? =)
автор: Shabie I•
18 февр. 2018 г.
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.
автор: J.-F. R•
18 февр. 2020 г.
Great course by Prof Ng. I had taken his Machine Learning course a few years ago, so expected high standards of content and assignment preparation - I was not disappointed. Staff is very responsive and helpful in forums as well. I highly recommend it. Taken as part of the DeepLearning specialization.
8 февр. 2020 г.
I loved this course as wel, I had a little bit less time to advance as steadily as I did with previous courses. So I had a little bit of trouble getting the context back when starting again each time. The next steps for me are putting what I learned into practice and basing myself on what I learned here.
автор: Pavel K•
5 февр. 2019 г.
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.
автор: Md A A A•
4 окт. 2020 г.
The course content is very good. This course seemed a little bit harder than other previous courses. There is lots of improvement opportunities for Coursera's Lab (Jypeter notebooks), every now and then it does not work i.e. cant submit the assignment, it's very very slow, its just not up to the mark.
автор: Akshay M P•
29 сент. 2020 г.
A very well organized introduction to the wonderland of Recurrent Neural Networks. The course takes the student through multiple use cases of various RNN architectures with practical advice on how and where to use them. The awesome programming assignments with excellent documentation is a highlight!
автор: CAMILO G Z•
26 янв. 2020 г.
With this course it's possible to conclude that recurrent neural networks are the most powerful variant of neural networks. Used in a many places, this course expleains ingishtfully how they work, what's the math behind them, and how different implementations function for different areas of research.
автор: Angad S•
16 февр. 2018 г.
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.