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Shweta Lalit

成为会员时间:2019

青铜联赛

1300 积分
Intermediate ML: TensorFlow on Google Cloud Earned Oct 17, 2019 EDT
Machine Learning APIs Earned Oct 7, 2019 EDT
面向机器学习的 BigQuery Earned Oct 2, 2019 EDT
机器学习简介:语言处理 Earned Oct 1, 2019 EDT
基准:数据、机器学习和 AI Earned Sep 30, 2019 EDT
在 Google Cloud 中使用 Kubernetes Earned Aug 26, 2019 EDT
DEPRECATED Cloud Architecture Earned Aug 26, 2019 EDT
基准:基础架构 Earned Aug 20, 2019 EDT
[DEPRECATED] OK Google: Build Interactive Apps with Google Assistant Earned Aug 1, 2019 EDT

TensorFlow is an open source software library for high performance numerical computation that's great for writing models that can train and run on platforms ranging from your laptop to a fleet of servers in the Cloud to an edge device. This quest takes you beyond the basics of using predefined models and teaches you how to build, train and deploy your own on Google Cloud.

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It's no secret that machine learning is one of the fastest growing fields in tech, and Google Cloud has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level course, you will get hands-on practice with machine learning APIs by taking labs like Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? Enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.

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想要仅使用 SQL 就能在几分钟内构建机器学习模型,而不是花费数小时?BigQuery 借助机器学习,数据分析师能够使用现有的 SQL 工具和技能创建、训练、评估机器学习模型,并使用这些模型进行预测, 从而实现机器学习的普及。在 本系列实验中,您将尝试不同的模型类型,并了解 如何构建出色的模型。

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众所周知,机器学习是发展最快的技术领域之一, Google Cloud Platform 在推动其发展方面发挥了重要作用。 GCP 提供了一系列 API,几乎可以满足任何机器学习作业的需求。在 本入门课程中,您将了解机器学习在语言处理方面的运用, 通过实操实验学习 如何从文本中提取实体,执行情感和语法分析,以及 使用 Speech-to-Text API 进行转写。

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大数据、机器学习和人工智能是当今计算领域的热门话题, 但这些领域的专业性很强,因而很难找到 入门资料。幸运的是,Google Cloud 在这些领域提供了方便用户使用的服务, 通过本入门级课程,您可以 开始学习使用 BigQuery、Cloud Speech API 和 Video Intelligence 等工具。

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Kubernetes 是最受欢迎的容器编排系统, Google Kubernetes Engine 专为支持 Google Cloud 中的托管式 Kubernetes 部署 而设计。在本高级课程中,您将亲自动手配置 Docker 映像、容器,并部署功能完备的 Kubernetes Engine 应用。 此课程将帮助您掌握在工作流中集成容器编排所需的 实用技能。 想要参加实操实验室挑战赛, 展示您的技能并检验所学知识?完成本课程后,不妨继续参与这项额外的 实验室挑战赛,赢得 Google Cloud 专属数字徽章。 该挑战赛位于在 Google Cloud 上部署 Kubernetes 应用课程的结尾处。

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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Cloud Architect Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.

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如果您是一位入门级云开发者, 在学习了“Google Cloud 基础知识”课程之后,想要寻求真正的实操机会,这门课程就是您的不二之选。您将获得宝贵的实操经验, 通过多个实验深入探索 Cloud Storage 以及 Monitoring 和 Cloud Functions 等其他关键应用服务。您将掌握一系列宝贵技能, 在 Google Cloud 的任何计划中,这些技能都能发挥作用。

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With Google Assistant part of over a billion consumer devices, this quest teaches you how to build practical Google Assistant applications integrated with Google Cloud services via APIs. Example apps will use the Dialogflow conversational suite and the Actions and Cloud Functions frameworks. You will build 5 different applications that explore useful and fun tools you can extend on your own. No hardware required! These labs use the cloud-based Google Assistant simulator environment for developing and testing, but if you do have your own device, such as a Google Home or a Google Hub, additional instructions are provided on how to deploy your apps to your own hardware.

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