课程信息
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第 3 门课程(共 4 门)

100% 在线

立即开始,按照自己的计划学习。

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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9 小时

建议:4 weeks of study, 4-5 hours/week...

英语(English)

字幕:英语(English)
User
学习Course的学生是
  • Data Scientists
  • Machine Learning Engineers
  • Chief Technology Officers (CTOs)
  • Data Engineers
  • Scientists

您将学到的内容有

  • Check

    Build natural language processing systems using TensorFlow

  • Check

    Process text, including tokenization and representing sentences as vectors

  • Check

    Apply RNNs, GRUs, and LSTMs in TensorFlow

  • Check

    Train LSTMs on existing text to create original poetry and more

您将获得的技能

Natural Language ProcessingTokenizationMachine LearningTensorflowRNNs
User
学习Course的学生是
  • Data Scientists
  • Machine Learning Engineers
  • Chief Technology Officers (CTOs)
  • Data Engineers
  • Scientists

第 3 门课程(共 4 门)

100% 在线

立即开始,按照自己的计划学习。

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9 小时

建议:4 weeks of study, 4-5 hours/week...

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 3 小时

Sentiment in text

13 个视频 (总计 30 分钟), 1 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
1 个阅读材料
News headlines dataset for sarcasm detection10分钟
1 个练习
Week 1 Quiz
2
完成时间为 3 小时

Word Embeddings

14 个视频 (总计 39 分钟), 5 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
5 个阅读材料
IMDB reviews dataset10分钟
Try it yourself10分钟
TensoFlow datasets10分钟
Subwords text encoder10分钟
Week 2 Wrap up10分钟
1 个练习
Week 2 Quiz
3
完成时间为 3 小时

Sequence models

10 个视频 (总计 16 分钟), 4 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
4 个阅读材料
Link to Andrew's sequence modeling course10分钟
More info on LSTMs10分钟
Exploring different sequence models10分钟
Week 3 Wrap up10分钟
1 个练习
Week 3 Quiz
4
完成时间为 3 小时

Sequence models and literature

14 个视频 (总计 27 分钟), 3 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
3 个阅读材料
link to Laurence's poetry10分钟
Link to generating text using a character-based RNN10分钟
Wrap up10分钟
1 个练习
Week 4 Quiz
4.6
163 个审阅Chevron Right

来自Natural Language Processing in TensorFlow的热门评论

创建者 GSAug 27th 2019

Excellent. Isn't Laurence just great! Fantastically deep knowledge, easy learning style, very practical presentation. And funny! A pure joy, highly relevant and extremely useful of course. Thank you!

创建者 AMSep 23rd 2019

Excellent course. Teaches NLP thoroughly, going from the basics such as tokenization and padding to complex topics such as word embeddings and sequence models (like RNNs, LSTMs and GRUs).

讲师

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Laurence Moroney

AI Advocate
Google Brain

关于 deeplearning.ai

deeplearning.ai is Andrew Ng's new venture which amongst others, strives for providing comprehensive AI education beyond borders....

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. Courses 1-3 are available now, with Course 4 launching in July....
TensorFlow in Practice

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