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学生对 deeplearning.ai 提供的 序列模型 的评价和反馈

4.8
27,359 个评分
3,266 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:

3226 - 序列模型 的 3250 个评论(共 3,266 个)

创建者 Mladen M

Jul 9, 2020

Programming assignment instructions are not well written (clear), and as a result it is easy to get stuck on something of little relevance to deep learning. Also, I would suggest that you make the lecture notes in written format available.

创建者 Chris M

Aug 21, 2019

The lectures cover the basic design of the models but don't help teaching you how to actually use them. I learned more by reading blogs to get the programming assignments to work then this course.

创建者 Ashley H

Sep 14, 2018

Lectures/Videos were excellent, the assignments were very poor (loads of errors in the code not corrected over 7 months since the course went live)

创建者 yuvaraj

Dec 11, 2020

The course videos were very lengthy and difficult to follow. Many topics discussed in course video were not part of programming assignment

创建者 Simeon S

Mar 18, 2020

Good introduction to the concepts. Really poor quality videos and exercises. Very frustrating when working on the assignments.

创建者 David L

Jun 28, 2020

Good lectures. Programming assignments are useless fill-in-the-blank exercises, you don't really learn much from them.

创建者 Thomas A

Oct 10, 2019

The programming assignments really are like pulling teeth. There's not really enough guidance leading up to them.

创建者 Mark

Oct 24, 2018

The course videos and the programming assignments were lacking. And there was no support in the forums.

创建者 Jeffrey S

Jun 2, 2018

Spent more time trying to work around a buggy grader than learning the underlying concepts.

创建者 Frank T

Oct 23, 2019

Too hard to understand compared to the previous coursed in this specification.

创建者 Hamid A

Nov 13, 2020

Was very difficult. please add more expiation of mathematical equations.

创建者 Sukeesh

Apr 18, 2020

Little unsatisfied with the final part of the specialization.

创建者 Clashing P

Sep 12, 2021

assignments are very hard and needs lots and lots of search

创建者 Arsh K

Aug 20, 2019

Lack of Keras training made it often hard to do layer code.

创建者 Tom T

Jan 9, 2020

This course needs more instruction on Keras.

创建者 Mark N

Feb 12, 2018

Poor explanation for alot of things

创建者 Milica M

May 10, 2020

boring and uninformative

创建者 João P B D

Jan 4, 2019

Too difficult.

创建者 Martin B

Mar 11, 2018

Needs work.

创建者 Alex L

Mar 5, 2018

I feel sad.

创建者 zhesihuang

Mar 3, 2019

sucks

创建者 Selina M

Aug 6, 2021

The course overall taught me new things, but I am still kinda unsure how to exactly use it.

The exercises and explanations weren't as enlightening as earlier and unfortunately left me rather confused, despite passing 100%. You definitely need to consult a lot of other sources for understanding the topic.

The last transformer exercise left me stunned though in how bad it was. When I understood something it contained obvious mathematical inconsistencies. It was the first time I needed the forum help, which is outside the coursera website and they force you to sign up in addition to coursera.

The tutor reacted fast but extremely patronising, going so far as pretending mistakes in the exercise didn't exist, but very eager to blame me for using an outdated version, that I wasn't using.

Did not enjoy the experience.

创建者 Aldiyar K

Mar 12, 2021

Oversimplifying material, such as not showing any math foundations and proofs, does not lead to an intrinsic understanding of the material as well as fill-the-gap assignments do not enhance comprehension.

I understand that the course is intended for the broad audience but will one be able to implement those Keras and TensorFlow algorithms on a moderately complex problem, which is the ultimate goal of these courses? Highly doubt it because the code is pre-written for students and step-by-step guide is provided. In my opinion, one could go straight to assignments and induct / deduct the answers.

创建者 Venkata D R S

Oct 19, 2020

I love Dr. Andrew, I seriously do. He has inspired me in the field of Deep Learning like no one else did. But I detest how this course is made so expensive and in a wrong direction. I subscribed and paid $225 and I still was not given a decent amount of time to finish the course, even when I asked for extension. If this is the way these courses are, its better of learning from youtube. It is not worth the money

创建者 Franjo I

May 10, 2020

Dry and uninformative. Immense space for improvement. Corrections should be made to videos instead of having numerous revisions comments after lecture. Some variables introduced haphazardly. Notation not explained well, some clashing with linear algebra conventions. Coding exercises are elementary hyper guided.