课程信息
52,740 次近期查看

Learner Career Outcomes

33%

完成这些课程后已开始新的职业生涯

38%

通过此课程获得实实在在的工作福利

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

完成时间大约为10 小时

建议:2-3 weeks of study, 8-10 hours/week...

英语(English)

字幕:法语(French), 巴西葡萄牙语, 德语(German), 英语(English), 西班牙语(Spanish), 日语...

您将获得的技能

Application Programming Interfaces (API)EstimatorMachine LearningTensorflowCloud Computing

Learner Career Outcomes

33%

完成这些课程后已开始新的职业生涯

38%

通过此课程获得实实在在的工作福利

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

完成时间大约为10 小时

建议:2-3 weeks of study, 8-10 hours/week...

英语(English)

字幕:法语(French), 巴西葡萄牙语, 德语(German), 英语(English), 西班牙语(Spanish), 日语...

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 7 分钟

Introduction

2 个视频 (总计 7 分钟)
2 个视频
Intro to Qwiklabs5分钟
完成时间为 3 小时

Core TensorFlow

19 个视频 (总计 72 分钟), 4 个测验
19 个视频
What is TensorFlow2分钟
Benefits of a Directed Graph5分钟
TensorFlow API Hierarchy3分钟
Lazy Evaluation4分钟
Graph and Session4分钟
Evaluating a Tensor2分钟
Visualizing a graph2分钟
Tensors6分钟
Variables6分钟
Lab Intro: Writing low-level TensorFlow programs16
Lab Solution8分钟
Introduction5分钟
Shape problems3分钟
Fixing shape problems2分钟
Data type problems1分钟
Debugging full programs4分钟
Intro: Debugging full programs15
Demo: Debugging Full Programs3分钟
3 个练习
What is TensorFlow?2分钟
Graphs and Sessions8分钟
Core TensorFlow20分钟
2
完成时间为 4 小时

Estimator API

18 个视频 (总计 67 分钟), 4 个测验
18 个视频
Estimator API3分钟
Pre-made Estimators5分钟
Demo: Housing Price Model1分钟
Checkpointing1分钟
Training on in-memory datasets2分钟
Lab Intro: Estimator API39
Lab Solution: Estimator API10分钟
Train on large datasets with Dataset API8分钟
Lab Intro: Scaling up TensorFlow ingest using batching35
Lab Solution: Scaling up TensorFlow ingest using batching5分钟
Big jobs, Distributed training6分钟
Monitoring with TensorBoard3分钟
Demo: TensorBoard UI28
Serving Input Function5分钟
Recap: Estimator API1分钟
Lab Intro: Creating a distributed training TensorFlow model with Estimator API51
Lab Solution: Creating a distributed training TensorFlow model with Estimator API7分钟
1 个练习
Estimator API18分钟
3
完成时间为 2 小时

Scaling TensorFlow models

6 个视频 (总计 29 分钟), 1 个阅读材料, 2 个测验
6 个视频
Why Cloud AI Platform?6分钟
Train a Model2分钟
Monitoring and Deploying Training Jobs2分钟
Lab Intro: Scaling TensorFlow with Cloud AI Platform50
Lab Solution: Scaling TensorFlow with Cloud AI Platform16分钟
1 个阅读材料
Cloud ML Engine is now Cloud AI Platform10分钟
1 个练习
Cloud AI Platform10分钟
完成时间为 2 分钟

Summary

1 个视频 (总计 2 分钟)
1 个视频
Summary2分钟
4.5
191 条评论Chevron Right

来自Intro to TensorFlow的热门评论

创建者 DWOct 17th 2018

pretty good. some of the code in the last lab could be better explained. also please debug the cloud shell, as it does not always show the "web preview" button ;) otherwise, good job!

创建者 SSJun 6th 2018

Nice introduce, might be more on introduce the model structure, because I still need to read additional notes to locate how to train my deep learning model online.

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关于 Machine Learning with TensorFlow on Google Cloud Platform 专项课程

What is machine learning, and what kinds of problems can it solve? What are the five phases of converting a candidate use case to be driven by machine learning, and why is it important that the phases not be skipped? Why are neural networks so popular now? How can you set up a supervised learning problem and find a good, generalizable solution using gradient descent and a thoughtful way of creating datasets? Learn how to write distributed machine learning models that scale in Tensorflow, scale out the training of those models. and offer high-performance predictions. Convert raw data to features in a way that allows ML to learn important characteristics from the data and bring human insight to bear on the problem. Finally, learn how to incorporate the right mix of parameters that yields accurate, generalized models and knowledge of the theory to solve specific types of ML problems. You will experiment with end-to-end ML, starting from building an ML-focused strategy and progressing into model training, optimization, and productionalization with hands-on labs using Google Cloud Platform. > By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <...
Machine Learning with TensorFlow on Google Cloud Platform

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