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學生對 deeplearning.ai 提供的 序列模型 的評價和反饋

4.8
27,217 個評分
3,243 條評論

課程概述

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....

熱門審閱

JY
2018年10月29日

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
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.

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2976 - 序列模型 的 3000 個評論(共 3,239 個)

創建者 shuieryin

2018年2月8日

soooo difficult...

創建者 sunlight

2018年7月13日

感觉没有前几次课程详细了,视频部分

創建者 Aditya M

2020年6月25日

Very good course

創建者 Pragyan P

2018年8月11日

It was tough :)

創建者 Enzo D

2018年4月13日

Very usefull!!!

創建者 guggilla s

2019年3月9日

easy to learn

創建者 Sayon S

2018年6月11日

A bit cryptic

創建者 Phoenix A

2018年3月28日

Good material

創建者 yanhang

2019年7月17日

very useful

創建者 Paul A

2019年2月24日

a bit hard!

創建者 Sonia D

2019年1月31日

Very Useful

創建者 BILLA N R

2020年4月18日

productive

創建者 Roberto J

2018年2月14日

Thank you.

創建者 Ariel H

2018年10月13日

Excellent

創建者 36 - O S

2020年6月1日

Average

創建者 Dave

2020年7月11日

good

創建者 teaching m

2020年4月5日

nice

創建者 VIGNESHKUMAR R

2019年10月24日

good

創建者 Shashank V M

2019年9月16日

Good

創建者 Yashwanth M

2019年7月23日

Good

創建者 Rahila T

2018年11月15日

Good

創建者 savinay s

2018年4月9日

good

創建者 krishna m s g

2018年3月22日

g

o

o

創建者 Aaradhya S

2020年4月25日

..

創建者 Natalia O

2019年10月4日

in comparison to the previous courses from this sequence, this one is even less structured - ptobably this is because even broader knowledge is tried to be shown in only 3 weeks, but i feel like a lot is skipped between videos (which are ok) and the tasks - in many assignment tasks in this course it is not very well explained what is meant to be done - i mean this especially in case of Keras objects. In many cases it is quite unclear how those classes are supposed to be handled in the context of our task. There are some hints but those are mostly links to documentation (btw, some of the links are no longer up to date), but it is often not too well explained which properties those objects have, what one can do etc. so one ends up with trying using those objects in different configuarations, then googling around, looking on the course forum for the right answer but it is very difficult to derive it. There should be more precise instructions regarding handling Keras objects - the examples in the documentation and in blogs are often much simpler than those from assignments so one ends up not knowing what is going on. In summary - there is a big jump and a big gap between the intuitions in videos (which btw are much more fuzzy than those in first cources in the specialization, the intuitions get more and more superfluous as one doesnt go into detail) and what is being done in the assignments. One thing i really liked about hte previous assignments was that when writing the code one could really know very well what is going on. And this is no longer the case in this course...