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學生對 deeplearning.ai 提供的 Sequence Models 的評價和反饋

4.8
26,174 個評分
3,088 條評論

課程概述

In the fifth course of the Deep Learning Specialization, you will become familiar with NLP models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language understanding, and more that have become possible with the evolution of sequence algorithms thanks to deep learning. By the end, you will be able to build and train Recurrent Neural Networks 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. DeepLearning.AI is proud to partner with NVIDIA Deep Learning Institute (DLI) to provide a programming assignment on Machine Translation with Deep Learning. Get an opportunity to build a deep learning project with leading-edge techniques using industry-relevant use cases. The Deep Learning Specialization is our 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 gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

熱門審閱

AM
2019年6月30日

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.

WK
2018年3月13日

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!

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351 - Sequence Models 的 375 個評論(共 3,059 個)

創建者 AKSHAY K C

2020年3月21日

The course was very well structured from the basics of RNN progressing slowly towards LSTM, GRU, word embedding and attention model finally. Kudos to the instructor and the team for providing such a good course on sequence models.

創建者 Meer H A

2019年6月2日

Thank you Andrew! Learned great things from this deep learning specialization course. The knowledge and certification I gained will help long way, in shaping my career. Thanks once again to the creators of this wonderful course :)

創建者 Carlos A C G

2020年6月11日

Amazing job once again by Andrew and his team. The world needs much more of this! Specially more implementations that can be put into use easily in real-life apps and projects. Now we know the theory, we can put it into practice.

創建者 ongole s s

2020年5月27日

I have learnt a lot from this course and it is very interesting to be part of this course as i understood the concepts of NLP in deep learning which is the most fascinating technology to learn and implement in real world problems

創建者 Sergio B S

2018年9月14日

The first week of this course is maybe the most harder week of all the Deep Learning Specialization. But, with Sequence Models I have understand infinite better the great possibilities of this techniques for improving the world.

創建者 Beltus W N

2020年10月19日

After finishing this course, I'm so fired up by the potential projects I can build with this knowledge that I feel adrenaline coursing through my veins. Thank you Prof. Andrew Ng. Thank you Deeplearning.ai team. You're the best.

創建者 Shashti K N M

2020年6月8日

The Course was Excellent. Sir's teaching was Excellent. I understood the techniques of Sequence Models and Natural Language Processing. The Programming Assignments were Excellent. The Deep Learning Specialization was Excellent.

創建者 George Z

2019年9月29日

Amazing course and what a finish line. I only with the graded assignments are revisited as few of them have bugs in them. Also I hope the Word2Vec algorithm and word embedding in general is explained better and with exact steps.

創建者 Sam D

2019年2月24日

Awesome course and specialization. Now, to implement everything I learned in my own programs, and of course I will be sure to revisit the videos until everything becomes second nature. Learn, program, improve and repeat. Thanks!

創建者 Himanshu G

2020年4月26日

This was particularly intensive course of this whole series, learned a lot.

Thanks to Prof. Andrew NG, accept a Natmastak Pranam from this Student of yours, will always be indebted for what I have learned here. You are the Best

創建者 Rahi A

2020年1月8日

I have many of books and blogs related to RNN, but was not clear and confident about it. And after studying only the first week video and lectures, I am so confident and happy that cant tell you!!! Thank you so much Andrew...;)

創建者 leonardo d

2019年12月4日

It seems like there are several and very useful RNN models. Many of them are very good at specific tasks, and if you take this course you will be abe to understand and implement many of them. It was a really amazing experience.

創建者 Sandeep P

2018年6月27日

An excellent introduction to the theory and practice on recurrent deep neural networks. Great usage of all the 4 courses in this series to culminate with this course as a great finish to deep learning theory and implementation.

創建者 Rafael E

2018年2月10日

Yet another amazing class! I'm so grateful for the existence of these classes. It makes mastering deep learning very much easier. My thanks to Andrew, and all others who have worked so hard to make this course possible! :-)

創建者 Hristo B

2019年2月25日

Most notably, an exercise guides one through the building of a recurrent network from scratch. More exercises show the value of different architectures and make the learner proficient in using neural network libraries (Keras).

創建者 Aparna D

2018年10月30日

This was quite a tough one.. But it was almost magical when the outputs of the assignment were successfully completed. Excellent. The discussion forums helped a lot, as the instructions were not very clear to novices like me.

創建者 Jeffrey T

2020年4月2日

Amazing course, Andrew Ng presents the material in a concise and intuitive manner. It would be nice to have access to all of the material needed to fool around with the assignments on our computers in an offline environment.

創建者 Dmitry N

2019年10月6日

Thank you for this wonderful sequence of courses! This whole concept is still a bit blurry for me, but as a lot of people during the interview have mentioned, one must simply exercise new skills to understand the technology.

創建者 Gopi P V R

2019年3月16日

It's great course to get concepts right and overview. It will be great if you add further programming assignments(other than partially coded ones) or resources as such where one can practice what he had learned as optional.

創建者 Nick S

2018年3月30日

Great choice of material, i would be happy to have one more week of that course to see more examples and have more time to familiarise with the concepts. All weeks were very useful and all the material was greatly explained.

創建者 Yousif M

2020年12月28日

I enjoyed all the courses of the specialization but I was looking forward to Sequence Models the most. I think a lot has been covered in this course and I can't wait to try working on projects with the knowledge I now have.

創建者 Severus

2020年6月5日

This course is good , I learn RNN,LSTM,GRU etc.Just one thing, the last assignment is hard to submit.I guess maybe there is a systematic problem that need to be solved. Everything except that is great. Thanks a lot, Andrew.

創建者 Seungbum H

2020年6月3日

This is an excellent course for a beginner like myself. I would like to thank Andrew for making this course available to everybody in the world. Thank you so much for your inspiring course. With best regards, Seungbum Hong.

創建者 Salman A

2020年4月23日

This course has helped me in developing an understanding for implementing sequence models through Recurrent Neural Networks that can be used in number of applications such as Natural Language Processing and Audio detection.

創建者 蕭博偉

2020年1月22日

A briefly introduction of Sequence Models to solve sequence problem, such as translation, speech reorganization..etc. Homework is also very helpful to understand what is going on step by step under Recurrent Neural Network.