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学生对 deeplearning.ai 提供的 序列模型 的评价和反馈

4.8
27,217 个评分
3,243 条评论

课程概述

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....

热门审阅

JY
Oct 29, 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.

AM
Jun 30, 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.

筛选依据:

201 - 序列模型 的 225 个评论(共 3,239 个)

创建者 Amit P

Dec 31, 2018

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.

创建者 Senthil K B

Jul 29, 2020

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.

创建者 michael z

Sep 29, 2019

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

创建者 Vladimir L

Jan 5, 2019

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!

创建者 RISHAV S

Jan 2, 2019

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.

创建者 Parab N S

Aug 25, 2019

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.

创建者 Rabih M

Nov 21, 2020

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.

创建者 Michael L

May 8, 2020

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!

创建者 Satyam D

Mar 27, 2019

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!

创建者 Rahuldeb D

Sep 23, 2018

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.

创建者 Navin S

Jul 15, 2020

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.

创建者 Nilanka W

Feb 18, 2018

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 !!

创建者 Jonathan L

Dec 18, 2018

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.

创建者 Harold M

Dec 9, 2018

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.

创建者 Miguel C N

Aug 25, 2021

A​fter having completed the Deep Learning Specialization i can say it was definitly worth it! Always top notch content, i have learned so much from these courses. I would strongly recommend them to anyone who has 0 to some knowledge of AI but has interest in the area. Thank you to the staff and everyone for this course.

创建者 Josh C

May 3, 2021

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,

创建者 Himanshu S

Jun 7, 2019

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.

创建者 Adam F

Nov 1, 2021

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.

创建者 Uday K B

Dec 12, 2019

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.

创建者 Sharath G

Feb 22, 2019

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. :)

创建者 Ahammad U

Nov 11, 2020

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.

创建者 Sanket D

Jun 1, 2020

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!

创建者 Anne G

Sep 13, 2019

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!

创建者 jaylen w

Nov 8, 2018

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.

创建者 Pavel K

Mar 31, 2018

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.