課程信息

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100% 在線

立即開始,按照自己的計劃學習。

第 4 門課程(共 4 門)

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

We recommend taking Course 1 of the TensorFlow in Practice Specialization first, or have basic familiarity with building models in TensorFlow.

完成時間大約為10 小時

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

英語(English)

字幕:英語(English)

您將學到的內容有

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    Use TensorFlow Serving to do inference over the web

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    Navigate TensorFlow Hub, a repository of models that you can use for transfer learning

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    Evaluate how your models work and share model metadata using TensorBoard

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    Explore federated learning and how to retrain deployed models while maintaining data privacy

您將獲得的技能

TensorFlow ServingMachine Learningfederated learningTensorFlow HubTensorBoard

100% 在線

立即開始,按照自己的計劃學習。

第 4 門課程(共 4 門)

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

We recommend taking Course 1 of the TensorFlow in Practice Specialization first, or have basic familiarity with building models in TensorFlow.

完成時間大約為10 小時

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

英語(English)

字幕:英語(English)

教學大綱 - 您將從這門課程中學到什麼

1

1

完成時間為 1 小時

TensorFlow Extended

完成時間為 1 小時
10 個視頻 (總計 16 分鐘), 3 個閱讀材料
10 個視頻
Introduction24
Serving3分鐘
Installing TF Serving1分鐘
W1 L1 P430
Setup for serving2分鐘
Serving1分鐘
Predictions41
Passing data to serving1分鐘
Getting the predictions back1分鐘
3 個閱讀材料
Installation link10分鐘
TF server running in colab10分鐘
Link to the colab10分鐘
2

2

完成時間為 5 小時

Sharing pre-trained models with TensorFlow Hub

完成時間為 5 小時
11 個視頻 (總計 20 分鐘), 4 個閱讀材料, 1 個測驗
11 個視頻
Introduction to TF Hub2分鐘
Transfer learning1分鐘
Inference1分鐘
Module storage2分鐘
Text based models1分鐘
Word embeddings1分鐘
Experimenting with embeddings1分鐘
Colab1分鐘
Classify cats and dogs1分鐘
Transfer learning1分鐘
4 個閱讀材料
Tensorflow Hub link10分鐘
Link to saved models10分鐘
pre-trained word embeddings10分鐘
MobileNet model details10分鐘
3

3

完成時間為 4 小時

Tensorboard: tools for model training

完成時間為 4 小時
10 個視頻 (總計 16 分鐘), 1 個閱讀材料, 1 個測驗
10 個視頻
Tensorboard scalars1分鐘
Callbacks42
Histograms59
Publishing model details1分鐘
Local tensorboard2分鐘
Looking at graphics in a dataset2分鐘
More than one image56
Confusion matrix2分鐘
Multiple callbacks1分鐘
1 個閱讀材料
tensorboard.dev10分鐘
4

4

完成時間為 22 分鐘

Federated Learning

完成時間為 22 分鐘
9 個視頻 (總計 22 分鐘)
9 個視頻
Training on mobile devices2分鐘
Data at the edge2分鐘
How it works2分鐘
Maintaining user privacy3分鐘
Masking2分鐘
APIs for Federated Learning2分鐘
Example of federated learning2分鐘
C4 W4 Outro59

講師

授課教師 Laurence Moroney 的圖片

Laurence Moroney

AI Advocate
Google Brain

關於 deeplearning.ai

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

關於 TensorFlow: Data and Deployment 專項課程

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 model. 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, use APIs to control how data splitting, and process all types of unstructured data. 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 AI. 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....
TensorFlow: Data and Deployment

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