课程信息

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第 3 门课程(共 4 门)
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中级

You should take the first 2 courses of the TensorFlow Specialization and be comfortable coding in Python and understanding high school-level math.

完成时间大约为14 小时
英语(English)
字幕:英语(English), 韩语

您将学到的内容有

  • Build natural language processing systems using TensorFlow

  • Process text, including tokenization and representing sentences as vectors

  • Apply RNNs, GRUs, and LSTMs in TensorFlow

  • Train LSTMs on existing text to create original poetry and more

您将获得的技能

Natural Language ProcessingTokenizationMachine LearningTensorflowRNNs
可分享的证书
完成后获得证书
100% 在线
立即开始,按照自己的计划学习。
第 3 门课程(共 4 门)
可灵活调整截止日期
根据您的日程表重置截止日期。
中级

You should take the first 2 courses of the TensorFlow Specialization and be comfortable coding in Python and understanding high school-level math.

完成时间大约为14 小时
英语(English)
字幕:英语(English), 韩语

讲师

提供方

deeplearning.ai 徽标

deeplearning.ai

教学大纲 - 您将从这门课程中学到什么

内容评分Thumbs Up92%(4,960 个评分)Info
1

1

完成时间为 3 小时

Sentiment in text

完成时间为 3 小时
13 个视频 (总计 30 分钟), 4 个阅读材料, 3 个测验
13 个视频
Introduction1分钟
Word based encodings2分钟
Using APIs2分钟
Notebook for lesson 12分钟
Text to sequence3分钟
Looking more at the Tokenizer1分钟
Padding2分钟
Notebook for lesson 24分钟
Sarcasm, really?2分钟
Working with the Tokenizer1分钟
Notebook for lesson 33分钟
Week 1 Wrap up21
4 个阅读材料
Check out the code!10分钟
Check out the code!10分钟
News headlines dataset for sarcasm detection10分钟
Check out the code!10分钟
1 个练习
Week 1 Quiz
2

2

完成时间为 4 小时

Word Embeddings

完成时间为 4 小时
14 个视频 (总计 39 分钟), 7 个阅读材料, 3 个测验
14 个视频
Introduction2分钟
The IMBD dataset1分钟
Looking into the details4分钟
How can we use vectors?2分钟
More into the details2分钟
Notebook for lesson 110分钟
Remember the sarcasm dataset?1分钟
Building a classifier for the sarcasm dataset1分钟
Let’s talk about the loss function1分钟
Pre-tokenized datasets43
Diving into the code (part 1)1分钟
Diving into the code (part 2)2分钟
Notebook for lesson 35分钟
7 个阅读材料
IMDB reviews dataset10分钟
Check out the code!10分钟
Check out the code!10分钟
TensorFlow datasets10分钟
Subwords text encoder10分钟
Check out the code!10分钟
Week 2 Wrap up10分钟
1 个练习
Week 2 Quiz
3

3

完成时间为 3 小时

Sequence models

完成时间为 3 小时
10 个视频 (总计 16 分钟), 7 个阅读材料, 3 个测验
10 个视频
Introduction2分钟
LSTMs2分钟
Implementing LSTMs in code1分钟
Accuracy and loss1分钟
A word from Laurence35
Looking into the code1分钟
Using a convolutional network1分钟
Going back to the IMDB dataset1分钟
Tips from Laurence37
7 个阅读材料
Link to Andrew's sequence modeling course10分钟
More info on LSTMs10分钟
Check out the code!10分钟
Check out the code!10分钟
Check out the code!10分钟
Exploring different sequence models10分钟
Week 3 Wrap up10分钟
1 个练习
Week 3 Quiz
4

4

完成时间为 3 小时

Sequence models and literature

完成时间为 3 小时
14 个视频 (总计 27 分钟), 5 个阅读材料, 3 个测验
14 个视频
Introduction1分钟
Looking into the code57
Training the data2分钟
More on training the data1分钟
Notebook for lesson 18分钟
Finding what the next word should be2分钟
Example1分钟
Predicting a word1分钟
Poetry!40
Looking into the code1分钟
Laurence the poet!1分钟
Your next task1分钟
A conversation with Andrew Ng1分钟
5 个阅读材料
Check out the code!10分钟
link to Laurence's poetry10分钟
Check out the code!10分钟
Link to generating text using a character-based RNN10分钟
Wrap up10分钟
1 个练习
Week 4 Quiz

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关于 TensorFlow in Practice 专项课程

Discover the tools software developers use to build scalable AI-powered algorithms in TensorFlow, a popular open-source machine learning framework. In this four-course Specialization, you’ll explore exciting opportunities for AI applications. Begin by developing an understanding of how to build and train neural networks. Improve a network’s performance using convolutions as you train it to identify real-world images. You’ll teach machines to understand, analyze, and respond to human speech with natural language processing systems. Learn to process text, represent sentences as vectors, and input data to a neural network. You’ll even train an AI to create original poetry! AI is already transforming industries across the world. After finishing this Specialization, you’ll be able to apply your new TensorFlow skills to a wide range of problems and projects. Looking for more advanced TensorFlow content? Check out the new TensorFlow: Data and Deployment Specialization....
TensorFlow in Practice

常见问题

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

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