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学生对 提供的 序列模型 的评价和反馈

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3,243 条评论


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....


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.

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.


2851 - 序列模型 的 2875 个评论(共 3,239 个)

创建者 EZ

Feb 18, 2018

Course is excellent. Assignment, however, could use some more refinement.

创建者 Attili S

Aug 12, 2020

It would be good to extend some more detailed explanation in this course

创建者 Sebastian M

Apr 7, 2019

need some reviewing in the optional parts of the programming assignments

创建者 Guan W

Mar 10, 2018

Excellent course content, but poor maintenance of programming assignment

创建者 Filip V

Feb 25, 2018

Provides good exposure to sequence models for NLP and speech processing.

创建者 Xirui Z

Apr 7, 2021

Instructions for labs are not clear enough, especially the layers part.

创建者 Mandeep S G

Jan 25, 2020

Great exercises but videos were slightly rushed. Overall a good course.

创建者 Vinod C

Apr 29, 2019

Good course. Feel a little bit rushed. Difficult to retain the concepts

创建者 Chen L

Mar 14, 2018

The content is great, but the programming exercises are full of errors.

创建者 Xiao

Mar 8, 2018

Some techniques for keras need to be clarified. Generally a good course

创建者 Jon M

Jul 7, 2021

I liked this particular set of lectures, too, now on to something new.

创建者 Vamvakaris M

Sep 8, 2019

It required coding on keras and tensorflow not appropriate introduced.

创建者 Rafael B d S

Aug 6, 2019

The Course is great! But the programming assignments has too many bugs

创建者 Gorden

Dec 12, 2018

it's very difficult to submit last programming exercise "trigger word"

创建者 Ishan S

Jun 27, 2020

More clarification on what we are doing in the programming exercises

创建者 Emanuel G

Dec 13, 2018

Great introduction to LSTMs, RNNs, GRUs, NLP and speech recognition.

创建者 Nilesh R

Mar 20, 2018

Great content but I felt it was bit rushed and squeezed in 3 weeks .

创建者 Alex M

Mar 14, 2018

The quality was a bit down but still very worthwhile and interesting

创建者 Vivek K

Jul 20, 2018

Great practical experience. Would have preferred a bit more theory.

创建者 Fady B

Jun 1, 2018

it covered a lot of interesting topics but it was a bit high level.

创建者 Alireza S

Jun 18, 2020

great course to understand intuition of sequence modeling for NLP.

创建者 guolianghu

Apr 5, 2020


创建者 Bobby A

Jul 2, 2019

Well explained, I feel like it could go a bit more in depth though

创建者 Martin T

Feb 13, 2018

Muy buen curso, resulta sumamente estimulante el ejemplo de woebot

创建者 Vikas C

Jun 20, 2019

The good course as the theoretical basis for RNN and other models