Chevron Left
返回到 Sequence Models

学生对 DeepLearning.AI 提供的 Sequence Models 的评价和反馈

4.8
31,140 个评分

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

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.

JY

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.

筛选依据:

1351 - Sequence Models 的 1375 个评论(共 3,832 个)

创建者 gayatri l

Jan 30, 2020

Gained some experience and insights to train models have fun.TRAIN,TEST,REPEAT

创建者 Tim W

Jan 21, 2020

Thank professor Andrew No for the courses. Wish to have more courses from him.

创建者 Alex K

Oct 14, 2019

Very good course, with a lot of useful and interesting topics in Deep Learning

创建者 Vu N M

Oct 25, 2018

The more data you have, the more power of you in this sequences neural network

创建者 Shuai W

Jun 2, 2018

Again, the state-of-the-art techniques are easily learned from Andrew's class.

创建者 Adrian L

Mar 21, 2018

Excellent class that explains very well how audio processing is done using RNN

创建者 Rui W

Feb 3, 2018

Great course again, it is hard to say goodbye! Hope to learn more from Andrew!

创建者 Richard J

Aug 27, 2022

This is the most challenge course, but I've learned lots on sequence nmodels.

创建者 Linh V

Dec 3, 2021

So much knowledge. But in last lab, it really hard to understand the exercise

创建者 Zeeshan A

Apr 22, 2021

This is an amazing course to learn the latest DL methods for sequential data.

创建者 Pablo J

Oct 1, 2020

Great lessons and projects to motivate further practical work on Recurrent NN

创建者 Abhijit H J

Jun 27, 2020

Good course. I liked it , Some more programming exercise will make it awesome

创建者 Geo T

Jun 6, 2020

Great Thanks. Excellent Course giving full of self confidence in Data Science

创建者 Julien L

May 17, 2020

Again an excellent course of this specialization. Very well done assignements

创建者 Aditya M

May 11, 2020

Thanks for preparing such a beautiful course. My basics have really improved!

创建者 Karel N N

Apr 4, 2019

Excellent courses, and a great teacher! Best regards and thank you very much!

创建者 Joaquin C D

Jul 15, 2018

Genial curso, he descubierto un nuevo mundo de aplicaciones de deep learning.

创建者 Adam S

Apr 8, 2018

Great course! Very step by step and very practical. The legend does it again.

创建者 Jennifer D

Mar 26, 2018

Extremely helpful instructional material. The course instructor is inspiring!

创建者 Hariharan V

Aug 21, 2025

Excellent course on deep learning with well curated hand-on labs and quizzes

创建者 Xuewen F

Jul 30, 2024

great. I like the teaching forms that videos followed by coding assignments.

创建者 KOLLA L

Sep 9, 2023

Thank you very much for this really helped me to get a better understanding.

创建者 Abhijeet D

Jul 12, 2022

It was a good course but due to some medical issues completed this one hurry

创建者 Lee Y Y

Mar 13, 2021

A little hard to completely follow, but the content is of very high-quality.