Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model.
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TensorFlow: Data and Deployment 专项课程deeplearning.ai课程信息
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第 3 门课程（共 4 门）
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中级
We recommend taking Course 1 of the TensorFlow in Practice Specialization first, or have a basic familiarity with building models in TensorFlow
完成时间大约为11 小时
英语（English）
字幕：英语（English）
您将学到的内容有
Perform efficient ETL tasks using Tensorflow Data Services APIs
Construct train/validation/test splits of any dataset - either custom or present in TensorFlow Hub Dataset library - using Splits API
Use different modules and functions of the TFDS API to prepare your data for training pipelines
Identify bottlenecks in your input pipelines and increase your workflow efficiency by input parallelization
您将获得的技能
Artificial Neural NetworkTensorflowExtraction, Transformation And Loading (ETL)Data PipelinesTensorFlow Datasets
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
We recommend taking Course 1 of the TensorFlow in Practice Specialization first, or have a basic familiarity with building models in TensorFlow
完成时间大约为11 小时
英语（English）
字幕：英语（English）
提供方
deeplearning.ai
Founded by Andrew Ng, DeepLearning.AI is an education technology company that develops a global community of AI talent.
教学大纲 - 您将从这门课程中学到什么
完成时间为 3 小时
Data Pipelines with TensorFlow Data Services
This week, you will be able to perform efficient ETL tasks using Tensorflow Data Services APIs
完成时间为 3 小时
10 个视频 （总计 21 分钟）, 4 个阅读材料, 2 个测验
10 个视频
Introduction1分钟
Popular Datasets2分钟
Data Pipelines58
Extract, Transform and Load3分钟
Versioning Datasets2分钟
Looking at the Notebook1分钟
Using TFDS in Keras to Train Fashion MNIST 3分钟
Horses or Humans in TFDS2分钟
Week 1 Wrap Up49
4 个阅读材料
Downloading the Coding Examples and Exercises10分钟
Try Out the Notebook Yourself10分钟
Try the Horses or Human Notebook10分钟
Grader Note10分钟
1 个练习
Week 1 Quiz30分钟
完成时间为 2 小时
Splits and Slices API for Datasets in TF
In this week, you will construct train/validation/test splits of any dataset - either custom or present in TensorFlow hub dataset library - using Splits API
完成时间为 2 小时
7 个视频 （总计 26 分钟）, 3 个阅读材料, 2 个测验
7 个视频
Introduction1分钟
Introduction to Splits API5分钟
Splits API Notebook Walkthrough5分钟
File Structure in TensorFlow Datasets1分钟
Feature Descriptors4分钟
TFRecord Colab Walkthrough5分钟
Week 2 Wrap Up1分钟
3 个阅读材料
Splits API Colab10分钟
TFRecord Colab 10分钟
Grader Note10分钟
1 个练习
Week 230分钟
完成时间为 3 小时
Exporting Your Data into the Training Pipeline
This week you will extend your knowledge of data pipelines
完成时间为 3 小时
21 个视频 （总计 44 分钟）, 5 个阅读材料, 2 个测验
21 个视频
Introduction22
Input Data1分钟
Basic Mechanics2分钟
Numeric and Bucketized Columns2分钟
Vocabulary and Hashed Columns, Feature Crossing2分钟
Embedding Columns2分钟
Introduction24
Notebook Walkthrough4分钟
Introduction19
Numpy, Pandas and Images2分钟
CSV3分钟
Text and TFRecord1分钟
Generators1分钟
Introduction17
Notebook walkthrough4分钟
Introduction1分钟
Using Numpy and Pandas2分钟
Image Data1分钟
CSV Data4分钟
Text Data2分钟
5 个阅读材料
Link to the Notebook10分钟
Link to the CNN Course10分钟
Link to the Notebook10分钟
CSV Colab10分钟
Link to the Course 10分钟
1 个练习
Week 3 Quiz30分钟
完成时间为 3 小时
Performance
You'll learn how to handle your data input to avoid bottlenecks, race conditions and more!
完成时间为 3 小时
22 个视频 （总计 44 分钟）, 2 个阅读材料, 3 个测验
22 个视频
Introduction36
ETL2分钟
What Happens When You Train a Model2分钟
Introduction25
Caching58
Parallelism APIs2分钟
Autotuning2分钟
Parallelizing Data Extraction2分钟
Best Practices for Code Improvements3分钟
A Few Words by Laurence34
A conversation with Andrew Ng1分钟
Introduction44
How to Start Using a Dataset2分钟
Implementation4分钟
File Access and Possible Problems in Data3分钟
Publishing the Dataset3分钟
Introduction18
Going Through the Colab- Part 12分钟
Going Through the Colab - Part 22分钟
Closing Words14
A conversation with Andrew Ng1分钟
2 个阅读材料
URLs10分钟
Link to the Colab10分钟
2 个练习
Week 4 Quiz
Publishing your Dataset Quiz
审阅
来自DATA PIPELINES WITH TENSORFLOW DATA SERVICES的热门评论
由 YO 提供May 16, 2020
Debugging exercises due to errors in indentation sounded stupid in the first place. But the joy of finally getting a "yes" in the assignment auto-grader beats them all.
由 PC 提供Apr 16, 2020
I understand why most of the students are furious about, but content wise, it one of those extremely helpful and important courses in Coursera. Really loved it!
由 MI 提供Apr 3, 2020
This course is quite essential, yet it is prepared too quickly? I had a hard time on Week 3 and Week 4 because the exercises are hard to grasp.
由 GL 提供Mar 2, 2020
Laurence cares deeply about the students. Not only about what they learn, but that they actually enjoy and learn it. What a fantastic teacher.
关于 TensorFlow: Data and Deployment 专项课程
Continue developing your skills in TensorFlow as you learn to navigate through a wide range of deployment scenarios and discover new ways to use data more effectively when training your machine learning models.
常见问题
我什么时候能够访问课程视频和作业？
讲座和作业的访问权限取决于您的注册类型。如果您以旁听模式参加课程，则可以免费查看大多数课程资料。要访问评分作业并获得证书，您需要在旁听期间或之后购买证书体验。如果看不到旁听选项：
- 课程可能不提供旁听选项。您可以尝试免费试用，也可以申请助学金。
- 课程可能会改为提供'完整课程，没有证书'。通过此选项，您可以查看所有课程材料、提交所要求的作业，以及获得最终成绩。这也意味着您将无法购买证书体验。
我订阅此专项课程后会得到什么？
您注册课程后，将有权访问专项课程中的所有课程，并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中，您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容，可以免费旁听课程。
Is financial aid available?
是的，Coursera 可以为无法承担费用的学生提供助学金。通过点击左侧“注册”按钮下的“助学金”链接可以申请助学金。您可以根据屏幕提示完成申请，申请获批后会收到通知。您需要针对专项课程中的每一门课程完成上述步骤，包括毕业项目。了解更多。
Why was Course 3: Data Pipelines with TensorFlow Data Service updated in October 2020?
- Changes in TensorFlow API: Since this Specialization was launched in early 2020, there have been changes to the TensorFlow API which affect the material in Weeks 1 and 2. With this refresh, you can access updated lectures, quizzes, and assignments.
- Changing the Difficulty Level of Assignments: Based on valuable learner feedback, we’ve revised the Week 4 assignments to ensure that you have a full grasp of the foundational principles and are well-prepared to tackle them.
完成课程后，我会获得大学学分吗？
此课程不提供大学学分，但部分大学可能会选择接受课程证书作为学分。查看您的合作院校，了解详情。Coursera 上的在线学位和 Mastertrack™ 证书提供获得大学学分的机会。
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