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Comentários e feedback de alunos de Sequence Models da instituição deeplearning.ai

4.8
estrelas
26,842 classificações
3,180 avaliações

Sobre o curso

In the fifth course of the Deep Learning Specialization, you will become familiar with sequence models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language processing (NLP), and more. By the end, you will be able to build and train Recurrent Neural Networks (RNNs) and commonly-used variants such as GRUs and LSTMs; apply RNNs to Character-level Language Modeling; gain experience with natural language processing and Word Embeddings; and use HuggingFace tokenizers and transformer models to solve different NLP tasks such as NER and Question Answering. The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career....

Melhores avaliações

WK
13 de Mar de 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!

AM
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.

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101 — 125 de 3,170 Avaliações para o Sequence Models

por Tian Q

6 de Jan de 2019

Great content! Andrew's lectures are great as always. The assignments are absolutely exciting and fun. Obviously the team put a tremendous effort on the programming exercises to make them doable for laymen yet not trivial. The exercises avoid using libraries (like Keras and TensorFlow) at the very beginning. Instead, they started with the more basic Numpy implementations. After these practice, I am able to grasp what each layer is actually doing.

My only suggestion is to correct some trivial typos in the Notebook.

por Marc S O

13 de Set de 2020

I like how it injects the idea of a subjective language/audio processing into a mathematical model learned by a computer. The whole team managing this class has been very careful in setting up the quizzes and machine problems to let the students get their hands dirty on machine learning projects. I gave 5 stars because it encourages people to read research papers, tells if a particular paper is hard to read, recommends papers that are easy to read. This way, more people can be interested in the world of research.

por James D M

13 de Fev de 2018

Thank you for helping me to get over the initial barrier to entry in NLP and audio data with this Sequence Models course. LSTM's are core to so many current technologies, and building them from scratch has provided me with good intuition for working with them. There was a good mix of numpy and Keras, as well as having the homework be clear enough to work through without getting stuck on minutia. It's always a pleasure to listen to Andrew Ng walk us through a problem with clarity, simplicity, and enthusiasm.

por Anders A

4 de Abr de 2019

The course is well thought and easy to follow. I regret not starting on this earlier in my quest to understand RNNs. It is the best source I found through shopping around. The courses is scheduled for three weeks, but is actually doable in an afternoon + a morning session if you have some python programming skills and enjoy 2x on your lectures. My one complaint is not with the course itself but the whole series. I mislike the subscription model for payments. I prefer a one time payment for life-time access.

por Maximiliano B

2 de Jan de 2020

In this last module of the specialization, you will learn in details how the recurrent neural networks works. I really enjoyed and had fun with the programing assignments specially the Emojify and the trigger word detection. After the course, you feel comfortable to read all papers mentioned as references throughout the course. Moreover, professor Andrew NG is awesome because he explains the content clearly, it is a pleasure to watch his videos and he provides everything you need to go the extra mile.

por tarun b

3 de Mar de 2018

Couldn't be more grateful for having the opportunity to take this specialization. The instructions were just at the right level of illustrating theory in practice, and the programming exercise at the right level to gain intuitions with implementation details. So many rights !!! Personally, I had the confidence that the syllabus is exhaustive and the callouts to research were just great. Overall ... excellent resource I will revisit often. Thank you to everyone who put this together and to Prof Ng.

por Vignesh S

22 de Out de 2019

Thank you, everyone, on the team for such an orchestration of the course. It was excellent to get to know the concepts of deep learning and it increased my interest in the field exponentially. A special thanks to Dr. Andrew NG for those explanations given in detail. This course was really interesting and it definitely overturned my attitude towards NLP as at first, I thought this is gonna be a difficult field of AI.

PS: Keep that ever-smiling face of yours the same Andrew Sir. Thanks a lot.

por David T

24 de Jun de 2020

Very effective mix of theory and practical examples, cemented by practice exercises in form of the programming assignments. The guided instructions of the programming assignments are as valuable as the lectures. I would recommend putting the "errata" readings *before* the videos containing the errors (as was done in an earlier course). I also notice that some quiz questions pick up on nuances that were quite underplayed in the lectures, but going back over my notes, did find them.

por Amey N

15 de Dez de 2019

Smooth and hands-on walkthrough of basics of NLP and speech recognition. The flow of the course is very well-designed.

After having completed this specialization I can confidently say that I have a much better understanding of Deep Learning than what I had before I underwent the specialization. This includes the depth and breadth of DL, various models, their challenges, advantages & disadvantages, end-to-end pipelines, optimization techniques, background calculus & math, et cetera...

por Brian H

21 de Mar de 2020

Amazing course overall. Prof Ng's diagrams are the clearest explanations of DL models I have found anywhere and it's that clear a ton of thought went into planning the notations. The assignments are exciting and surprisingly fun. One could say that there is a little too much handholding throughout the assignments, but I understand that this course is more about the heuristics. Again, it's fantastic course overall and the resources provided throughout are truly unique to Coursera!

por Kuntal C

20 de Out de 2018

This was my first AI course and I really made significant progress in my understanding of foundations of deep learning with this. Thanks to Professor Andrew's very informative course videos, grasping the complex concepts became possible. The quizzes and the assignments were challenging, made possible for me to use logic and develop new coding skills to go at it. I would recommend this course to everyone interested in AI/ML. Thanks to Professor Andrew for making this course.

por Mohd F

23 de Jul de 2019

This is an amazing course, it Provides a great Help...i have learned lots n lots of stuff about NLP, Learn about recurrent neural networks that work extremely well on temporal data, word vector representations and embedding layers --that are explained in a concise manner, and more importantly I love the Attention mechanism, the model that understand where it should focus...... its attention given a sequence of inputs.... amazing amazing ..highly Recommended.... Thankyou

por alrojas68

9 de Jan de 2019

This course was a great introduction to the world of RNNs. Starting from basic sequence models all the way through RNNs constructed with Convolutional layers, LTSM layers, GRU layers and wrapping up with the Attention Algorithm. It is great base work to start a Deep Learning career. The course is very well structured and the resources in the forums were always life-saving. Very grateful for this course and I am waiting for the Advanced Specialization from Deeplearning.ai

por Janith G

9 de Nov de 2019

Really good course for RNNs with NLP. Recommended to anyone who has completed the first four courses of the specialization. A thing to notice is that the last programming assignment is really hard to save and submit to your servers though it was pretty well organized.

Also I would like to thanks Coursera and Prof. Andrew for bringing ML DL and AI to a level that a student can understand without any useless long mathematical proofs. Thank you for giving this opportunity.

por Artem D

12 de Jun de 2019

I really liked the whole Specialization, it is great: clear and interesting!

But the last course seemed very difficult to me: may be I've been pretty overhelmed (I've completed the spec in less then in a month), may the topics are much harder then in previous course, may be Andrew Ng wanted to cover too much items in short time. It seemed to me hat CV course was more clear.

Nevertheless I rate this course @5 stars and beleive that the spec is PERFECT!

THANK YOU, ANDREW!

por Carlos V

14 de Fev de 2018

Another Excellent Course from Professor Andrew Ng. The detail in the explanations are excellent, and the provided exercises using Jupyter are super fun to complete and put to the test your knowledge offering you at the same time a library of ideas and models to use in your future projects. I enjoyed this last course in the specialization quite a lot, thanks very much to Andrew Ng and the Staff from Coursera. I hope to see more courses like this in the future.

Thanks

por Rodolfo V d A

7 de Ago de 2020

I love this course. Maybe about 1 and half year I was trying to learn DL. I thought about giving up because I wasn't able to learn, so, in May of this year 2020, Coursera opened its courses to undergraduates. I do not thought twice, at the same hour that I knew that news about free courses, I began this. Then, after that time I want to thank to Professor Ng and all colaborators on that site. One day I will be one of student of Professor Andrew Ng in Stanford.

por Prithvi J

5 de Mar de 2020

A greatly knowledgeable course! I learned a lot about Natural Language Processing and explored RNNs, LSTMs, Word Embeddings, Seq2Seq Models, Attention Mechanism, etc. The course focuses more on the concepts along with providing the essential math. It was fun to implement Language Models, Neural Machine Translation & Speech Recognition. I would surely recommend this course to the ones who are diving into the world of NLP, and need a perfect introduction to it.

por Huanglei P

31 de Jul de 2018

This end course is a little more complicated than the previous ones, especially in programming homework. However, it also inherits the merits of the special, gives learners the basic framework of sequence models. What impresses me most is the lesson of "Debiasing word embeddings", it shows that AI could be designed to do more against human stale thoughts, which sets up a good principle for designing AI. Yes, it should be taught to new learners of AI.

por Andres G

22 de Mar de 2020

Finally... Every piece of effort was worth it! After so many hours, now I understand how proud we can fell of completing these amazing courses! The best one I have tried so far, definitely made a difference in my professional views but above all, it confirmed my expectations: this is the activity sector where I want to develop, the work in which I want to grow without any doubt.

Thanks Andrew. Thanks Team. Thanks to everyone who made this possible.

por Marcus H

26 de Set de 2020

This regards all 5 courses of the DL specialisation.

1st of all: great work, it gives a much broader perspectives.

Room for improvement: sometimes the assignments become much of a "Python riddle" where one has to fiddle a lot with language technicalities and loses time for actually playing with the DL subject

2nd: please improve the submitting and savin g behaviour of the notebooks in the new LAB system. It is really painfully slow and unstable.

por ANSHUMAN S

25 de Jun de 2019

This was the most difficult and most interesting course i had in all of the five deeplearning.ai courses

but after doing all the 7 assignments i feel like i learned a lot and encountered with some of the amazing thing which i wondered how they are done . Once again I thanks to Andrew Sir and other teachers for beautiful lectures and perfect quizzes assigments and at last a heartly congrats to Coursera for giving this platform to me.

Thank You!

por Mihai L

21 de Mar de 2018

Will give this course also 5 stars. The assignments were easy but required some knowledge of Keras. So you have to invest some time on their site.Otherwise it's like fitting pieces in a bigger puzzle. Most pieces are already layed out for you .. you need to just fit your small ones.

I realize though that deep learning requires a lot of practice and experimentation and completing this course (and specialization) is just a tiny first step ..

por P S R

12 de Fev de 2018

Course contents and coverage was best. Duration of 3 weeks is little too short to really understand all the details of programming exercises. May be extend this to 4 to 5 weeks and spend little more time on speech recognition, music generation and other audio data processing would have helped.

Unlike all other earlier modules, this one had many issues with grader and many errors in note book templates. Hope these will be addressed in future.

por James B

1 de Mai de 2018

Wonderful course, expert instruction from Prof. Ng. I can't recommend the Specialization enough.

The choices of architecture and of hyperparameters for the assignments' network could have used further explication. Another desire left unfulfilled was that I would want the sequence models course doubled in all dimensions, ie lectures, assignments, etc. It was all over too quickly with questions lingering. Further study required!