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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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19 小时
英语（English）
字幕：英语（English）
您将学到的内容有
Leverage built-in datasets with just a few lines of code
Use APIs to control how you split your data
Process all types of unstructured data
您将获得的技能
TensorflowMachine Learning
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19 小时
英语（English）
字幕：英语（English）
提供方
deeplearning.ai
deeplearning.ai is Andrew Ng's new venture which amongst others, strives for providing comprehensive AI education beyond borders.
教学大纲 - 您将从这门课程中学到什么
完成时间为 5 小时
Data Pipelines with TensorFlow Data Services
You'll learn about the types of data that you would normally come across when doing machine learning.
完成时间为 5 小时
14 个视频 （总计 27 分钟）, 2 个阅读材料, 2 个测验
14 个视频
Introduction1分钟
Popular datasets2分钟
Data pipelines58
Extract, transform, load3分钟
Versioning datasets2分钟
Looking at the notebook1分钟
Introduction43
Legacy API and Subsplits5分钟
Splits API (S3)2分钟
Introduction22
Legacy API in code1分钟
Splits API (S3) in code1分钟
Week 1 wrap up43
2 个阅读材料
Downloading the Coding Examples and Exercises10分钟
Try out the notebook yourself10分钟
1 个练习
Week 1 Quiz
完成时间为 6 小时
Exporting your data into the training pipeline
This week you’re going to start looking at the code for using the data with input pipelines!
完成时间为 6 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
Numpy and Pandas2分钟
Images1分钟
CSV4分钟
Text2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 tokenization10分钟
1 个练习
Week 2 Quiz
完成时间为 4 小时
Performance
How you load your data into your model can have a huge impact on how efficiently the model trains. You'll learn how to handle your data input to avoid bottlenecks, race conditions and more!
完成时间为 4 小时
11 个视频 （总计 20 分钟）
11 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
1 个练习
Week 3 Quiz
完成时间为 5 小时
Publishing your datasets
This week let’s learn about how you can share your data with the world in a way that’s easy for others to consume!
完成时间为 5 小时
11 个视频 （总计 24 分钟）, 2 个阅读材料, 2 个测验
11 个视频
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 (1)2分钟
Going through the colab (2)2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
1 个练习
Week 4 Quiz
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.
In this four-course Specialization, you’ll learn how to get your machine learning models into the hands of real people on all kinds of devices. Start by understanding how to train and run machine learning models in browsers and in mobile applications. Learn how to leverage built-in datasets with just a few lines of code, learn about data pipelines with TensorFlow data services, use APIs to control data splitting, process all types of unstructured data and retrain deployed models with user data while maintaining data privacy. Apply your knowledge in various deployment scenarios and get introduced to TensorFlow Serving, TensorFlow, Hub, TensorBoard, and more.
Industries all around the world are adopting Artificial Intelligence. This Specialization from Laurence Moroney and Andrew Ng will help you develop and deploy machine learning models across any device or platform faster and more accurately than ever.
This Specialization builds upon skills learned in the TensorFlow in Practice Specialization. We recommend learners complete that Specialization prior to enrolling in TensorFlow: Data and Deployment.
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