課程信息
14,358 次近期查看

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立即開始,按照自己的計劃學習。

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中級

完成時間大約為7 小時

建議:1 week of study, 5-7 hours/week...

英語(English)

字幕:英語(English)

您將獲得的技能

BigqueryMachine LearningGoogle Cloud PlatformCloud Computing

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為7 小時

建議:1 week of study, 5-7 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
完成時間為 6 分鐘

Introduction

2 個視頻 (總計 6 分鐘)
2 個視頻
Qwiklabs Overview5分鐘
完成時間為 21 分鐘

Introduction to Machine Learning

6 個視頻 (總計 21 分鐘), 1 個測驗
6 個視頻
Demo: Google Photos2分鐘
What is deep learning?41
ML Applications for Business3分鐘
ML Terms: Instances, Features, Labels3分鐘
The Spectrum of ML Tools3分鐘
1 個練習
Introduction to Machine Learning
完成時間為 2 小時

Pre-trained ML APIs

9 個視頻 (總計 52 分鐘), 2 個測驗
9 個視頻
Demo: Cloud Translate and Vision APIs5分鐘
Demo: Natural Language Processing API3分鐘
Collaborative Notebooks in the Cloud5分鐘
Demo: Cloud Datalab with BigQuery and Google Analytics7分鐘
Accessing BigQuery datasets from Cloud Datalab15分鐘
Visualizing Datasets in Charts1分鐘
Lab Overview28
Lab Walkthrough10分鐘
1 個練習
Notebooks in the Cloud10分鐘
2
完成時間為 2 小時

Creating ​ML Datasets in BigQuery

8 個視頻 (總計 35 分鐘), 2 個測驗
8 個視頻
Choosing good features8分鐘
Exploring and Preprocessing Data1分鐘
Demo: Exploring and Preprocessing Data6分鐘
Other Tools for Creating Data Pipelines50
Knowing the Unknowable4分鐘
Creating Repeatable Dataset Splits2分鐘
Lab Solution: Creating Repeatable Dataset Splits9分鐘
1 個練習
Intro to Machine Learning10分鐘
完成時間為 4 小時

Creating ML Models in BigQuery

6 個視頻 (總計 54 分鐘), 1 個閱讀材料, 3 個測驗
6 個視頻
Phases of Model Building2分鐘
Demo: Predicting Taxi Cab Fare10分鐘
Demo: Creating a Classification Model12分鐘
Lab Intro: Predicting Visitor Return Purchases with BigQuery2分鐘
Lab Solution: Predicting Visitor Return Purchases in BigQuery20分鐘
1 個閱讀材料
BigQuery ML Resources10分鐘
1 個練習
BigQuery ML
完成時間為 3 分鐘

End of Course Recap

1 個視頻 (總計 3 分鐘)
1 個視頻
4.7
35 個審閱Chevron Right

67%

完成這些課程後已開始新的職業生涯

60%

通過此課程獲得實實在在的工作福利

14%

加薪或升職

來自Applying Machine Learning to your Data with GCP的熱門評論

創建者 MBJan 22nd 2019

Enjoyed. I would add more in-depth ML part for BigQuery and different scenario. it also good to explain metric how and how to choose right features etc

創建者 LLAug 11th 2018

The instructor Evan is super great to rolling out machine learning in an easy /understandable way. hope he can tech more in-depth of machine learning.

關於 Google 云端平台

We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success....

關於 From Data to Insights with Google Cloud Platform 專項課程

Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course! This four-course accelerated online specialization teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The courses feature interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The courses also cover data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization. This specialization is intended for the following participants: ● Data Analysts, Business Analysts, Business Intelligence professionals ● Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform To get the most out of this specialization, we recommend participants have some proficiency with ANSI SQL. >>> 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 <<<...
From Data to Insights with Google Cloud Platform

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