课程信息

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5 小时

建议:1 semana de estudo, de 8 a 12 horas por semana...

巴西葡萄牙语

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

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5 小时

建议:1 semana de estudo, de 8 a 12 horas por semana...

巴西葡萄牙语

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 11 分钟

Este é o "Serverless Machine Learning on Google Cloud Platform"

...
2 个视频 (总计 5 分钟), 1 个测验
2 个视频
Considerações sobre machine learning2分钟
1 个练习
Pré-teste do curso de machine learning6分钟
完成时间为 3 小时

Módulo 1: Primeiros passos com machine learning

...
21 个视频 (总计 109 分钟), 2 个测验
21 个视频
Tipos de ML3分钟
O canal de ML2分钟
Variantes do modelo de ML7分钟
Como classificar um problema de ML2分钟
Como usar machine learning (ML)8分钟
Otimização9分钟
Um playground de rede neural18分钟
Como combinar atributos3分钟
Engenharia de atributos3分钟
Modelos de imagem5分钟
ML eficaz2分钟
Quais são os elementos de um bom conjunto de dados?5分钟
Métricas de erro3分钟
Precisão2分钟
Precisão e recall5分钟
Como criar conjuntos de dados de machine learning3分钟
Como dividir conjuntos de dados6分钟
Python Notebooks1分钟
Visão geral do laboratório Como criar conjuntos de dados de ML3分钟
Revisão do laboratório Como criar conjuntos de dados de ML2分钟
1 个练习
Teste do módulo 18分钟
完成时间为 5 小时

Módulo 2: Criação de modelos de ML com o TensorFlow

...
15 个视频 (总计 65 分钟), 5 个测验
15 个视频
O que é o TensorFlow?5分钟
Principais características do TensorFlow5分钟
Visão geral do laboratório Primeiros passos com o TensorFlow7
Revisão do laboratório TensorFlow10分钟
API Estimator8分钟
Machine learning com o tf.estimator15
Revisão do laboratório Estimator7分钟
Como criar ML eficaz6分钟
Introdução ao laboratório Refatoração para adicionar a criação de lotes e recursos38
Revisão do laboratório Refatoração4分钟
Treine e avalie4分钟
Monitoramento1分钟
Introdução ao laboratório: Treinamento e monitoramento distribuídos2分钟
Revisão do laboratório: Treinamento e monitoramento distribuídos7分钟
1 个练习
Teste do módulo 28分钟
完成时间为 2 小时

Módulo 3: Escalonamento de modelos de ML com o Cloud ML Engine

...
7 个视频 (总计 28 分钟), 2 个测验
7 个视频
Por que usar o Cloud ML Engine?6分钟
Fluxo de trabalho de desenvolvimento1分钟
Como empacotar o treinador3分钟
TensorFlow Serving3分钟
Laboratório: Como escalonar ML39
Revisão do laboratório: Como escalonar ML10分钟
1 个练习
Teste do módulo 34分钟
完成时间为 3 小时

Módulo 4: Engenharia de atributos

...
16 个视频 (总计 92 分钟), 2 个测验
16 个视频
Atributos bons7分钟
Causalidade8分钟
Numérico5分钟
Exemplos suficientes7分钟
Dados brutos para os atributos1分钟
Atributos categóricos8分钟
Cruzamento de atributos3分钟
Como criar intervalos3分钟
Amplitude e profundidade5分钟
Onde aplicar a engenharia de atributos3分钟
Visão geral do laboratório Engenharia de atributos3分钟
Revisão do laboratório Engenharia de atributos10分钟
Ajuste de hiperparâmetro e demonstração15分钟
Níveis de abstração de ML4分钟
Resumo1分钟
1 个练习
Teste do módulo 46分钟

关于 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....

常见问题

  • 注册以便获得证书后,您将有权访问所有视频、测验和编程作业(如果适用)。只有在您的班次开课之后,才可以提交和审阅同学互评作业。如果您选择在不购买的情况下浏览课程,可能无法访问某些作业。

  • 您购买证书后,将有权访问所有课程材料,包括评分作业。完成课程后,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。

  • Before enrolling in this course, participants should have roughly one (1) year of experience with one or more of the following:

    • Knowledge of Google Cloud Platform

    • Big Data & Machine Learning Fundamentals to the level of "Google Cloud Platform Big Data and Machine Learning Fundamentals" on Coursera

    • Knowledge of BigQuery and Dataflow to the level of "Serverless Data Analysis with Google BigQuery and Cloud Dataflow" on Coursera

    • Knowledge of Python and familiarity with the numpy package

    • Knowledge of undergraduate-level statistics to the level of a Basic Statistics course on Coursera

  • To be eligible for the free trial, you will need:

    - Google account (Google is currently blocked in China)

    - Credit card or bank account

    - Terms of service

    Note: There is a known issue with certain EU countries where individuals are not able to sign up, but you may sign up as "business" status and intend to see a potential economic benefit from the trial. More details at: https://support.google.com/cloud/answer/6090602

    More Google Cloud Platform free trial FAQs are available at: https://cloud.google.com/free-trial/

    For more details on how the free trial works, visit our documentation page: https://cloud.google.com/free-trial/docs/

  • If your current Google account is no longer eligible for the Google Cloud Platform free trial, you can create another Google account. Your new Google account should be used to sign up for the free trial.

  • View this page for more details: https://cloud.google.com/free-trial/docs/

  • Yes, this online course is based on the instructor-led training formerly known as CPB102.

  • The course covers the topics presented on the certification exam, however we recommend additional preparation including hands-on product experience. The best preparation for certification is real-world, hands-on experience. Review the Google Certified Professional Data Engineer certification preparation guide for further information and resources at https://cloud.google.com/certification/guides/data-engineer/

  • Google’s Certification Program gives customers and partners a way to demonstrate their technical skills in a particular job-role and technology. Individuals are assessed using a variety of rigorously developed industry-standard methods to determine whether they meet Google’s proficiency standards. Read more at https://cloud.google.com/certification/

还有其他问题吗?请访问 学生帮助中心