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学生对 deeplearning.ai 提供的 Sequence Models 的评价和反馈

4.8
26,871 个评分
3,186 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

WK
Mar 13, 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
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:

251 - Sequence Models 的 275 个评论(共 3,176 个)

创建者 Leonardo E T C

Mar 29, 2021

In my opinion, this module was a little more complex than the previous ones, however, it has been an excellent course to deepen my knowledge in recurrent neural networks and close this specialization program in deep learning. Thank you very much, Dr. Andrew Ng and deeplearningai!!!!

创建者 Liyan X

Jun 3, 2018

Great course with interesting exercises. One can really see the amount of effort being put into creating the assignment material, so they are at a suitable level and with a lot to take away, and the students have a good understanding of details through practice. Really appreciated.

创建者 anand k

Apr 2, 2020

the programing assignment ins WEEK 1 was a bit ambiguous in nature. helped me improve my debugging skills.

Also a huge thank you to MENTOR Mr. GEOFF for the instant support to all my queries. His way of providing HINTS lead me to finally complete the course. a BIG thank you to him.

创建者 Manhal R

Jun 21, 2020

More easier to understand than the ConvNets course!

Week 1 and 2 took me a little time to get through. Week 3 is easy.

For better understanding, don't forget to download the notebooks and practice on your own local Jupyter notebook while using the assignment notebook as a reference.

创建者 Jayash K

Jul 6, 2018

This is a great course. It provides a good introduction to RNNs and how they are used in sequence modeling. Introduction to GRU, LSTMs, BiRNNs, attention model is great way to learn these in depth. The exercises are designed to make you familiar with the internals of these layers.

创建者 Dong Z

Aug 18, 2020

At the beginning this is very counter-intuitive. But later on when I am on the final assignment, I finally realized that we are not focusing on gradient descent, but architecture building and training set assembling! When everything start to make sense, it is really intriguing.

创建者 Kyung-Hoon K

Apr 29, 2020

This course made me have great understanding around the Sequence Models such as GRU, LSTM, Attention, etc. I had a lot of fun while completing programming exercises such as Trigger word detection. As always, it was one of the best class ever. Thanks Professor Andrew Ng and all-!

创建者 Vladimir B

Mar 14, 2018

Very good course. In quite short time you get understanding of a lot of principles and intuitions. The pace is good, explanations are consistent and clear, top-down approach from generic to specific, from simple to complex, very good instructional videos and interesting projects

创建者 kpb

Mar 2, 2018

Remarkably lucid exposition of complex learning architectures with directly applicable programming exercises. Highest recommendation. Thanks to the deep learning.ai staff for putting this entire specialization together and sharing their abundantly clear mastery of the subjects.

创建者 Tun C

Aug 28, 2018

Some of the lectures were not quite up to par with professor Ng's standard. Some of the programming assignments were hard to follow and missing some details. Nevertheless, I came away with good understanding of sequence models and RNN. I can't thank enough. 5 stars from me.

创建者 Julia C

May 27, 2019

This is very logical and especially the addition of probability between the words to improve predictions. It will be interesting to compare language , which language is easier to predict and why and study backward- how human creates them. We might learn something unexpected.

创建者 Ayush G

Jun 27, 2020

The lectures were super informative. It's almost unreal how easily he explains such difficult concepts, such they look a child's play. The coding assignments are incredibly informative and super interesting. I am very thankful for this specialization that it taught me so much

创建者 Andrew M

Jul 9, 2019

Before starting the course, I wanted to have a strong knowledge of the basics of Natural Language Processing as I wanted to specialize in this domain. I am thoroughly satisfied at the end of this course. This course has given me the confidence to dive deeper into this domain.

创建者 kk s

Mar 30, 2019

Course of lectures are excellent, but please fix the following problem

week 1 Programming Assignments

Improvise a Jazz Solo with an LSTM Network - v3

Dimensionality in djmodel()

https://www.coursera.org/learn/nlp-sequence-models/discussions/weeks/1/threads/NAoSHgf0Eei8aw6tWi-efA

创建者 Anurag S

Jun 1, 2020

I'll remain forever indebted to Andrew and his team for preparing this rigorous course. I can imagine the effort put in designing video lectures, going through research papers, crafting out these well-knit coding exercises. He has democratized AI and education in true sense.

创建者 Lucas S

Jan 21, 2019

I appreciate all the hard work and effort Andrew and his team puts in all his material.

I had hard time with most of Keras homework’s, I think it's hard to get the overall logic of a framework without an extensive explanation.

Besides that, the topics discussed are amazing.

创建者 Haider k

Dec 8, 2019

A great introduction to Recurrent Neural Network models with lots of examples (text generation, music generation, sentiment analysis, word embedding, speech recognition, attention-based machine translations etc.). Thanks a lot to Andrew and the team for this awesome course.

创建者 Fang S

Sep 12, 2018

Andrew, again explained complicated structures very clearly. The first week might be a bit overwhelming and you might get lost with huge information overflow, but trust me, in week2 and week3 you will see how the dots are connected. Thank you Andrew for this amazing course.

创建者 ABHINAV G

Feb 15, 2020

Thanks for making this course! I have been through all the courses in this specialization, and they are really excellent! Andrew has a great way of explaining things simply. It was easier for me to look at a couple of research papers after having gone through the lectures.

创建者 Mohamad K

Feb 26, 2019

Prof Andrew such a great person. He teaching from the heart where 99 % of Prof not doing it today.

He summarized Deep learning+ Computer vision+ NLP in easy way. I am thankful for Coursera and Prof Andrew. I strongly recommend this course and all his courses to everybody .

创建者 Akanksha D

Sep 26, 2018

Awesome. But the programming assignments need to be less erroneous and lectures and assignments could contain more technical and mathematical details to build the foundations. The programming assignments could be designed to allow the students to do more that spoonfeeding.

创建者 Alouini M Y

Feb 20, 2018

This was for me the best course on the deeplearning.ai series since I am a complete novice regarding sequence models. Nonetheless, I have managed to learn a lot and the material was very good (with often state of the art techniques). The assignments were excellent as well!

创建者 Aleksa G

Jan 20, 2019

I really liked this last course as I did not have much experience with NLP and with audio in general, as I did have with computer vision and image processing. The keyword detection model is really cool! After this specialization I am starting to build my own ML projects!

创建者 Raivis J

Mar 18, 2019

This is the hardest course in the specialisation, and may take some extra effort. For practical assignments I recommend getting familiar with Keras syntax and workflow, as here there is little hand-holding here,. the focus is on actual model architecture and algorithms.

创建者 Zein S

Feb 15, 2018

This is not a good course, and even not a good tutor.. It is a great course and Andrew is really incredible tutor... I like this course so much and got tons of benefits...

I am so happy to take this course..

PS: You can add this review to the sentiment analysis data set