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Niran N

成为会员时间:2019

白银联赛

7400 积分
DEPRECATED Explore Machine Learning Models with Explainable AI Earned Nov 4, 2020 EST
在 Google Cloud 使用機器學習 API Earned Nov 4, 2020 EST
使用 BigQuery ML 為預測模型進行資料工程 Earned Nov 4, 2020 EST
從 BigQuery 資料取得深入分析結果 Earned Oct 29, 2020 EDT
建構安全的 Google Cloud 網路 Earned Oct 29, 2020 EDT
Automate Deployment and Manage Traffic on a Google Cloud Network Earned Oct 29, 2020 EDT
在 Google Cloud 為機器學習 API 準備資料 Earned Oct 29, 2020 EDT
在 Google Cloud 部署 Kubernetes 應用程式 Earned Oct 19, 2020 EDT
Google Cloud 中的 Kubernetes Earned Oct 10, 2020 EDT
DEPRECATED Cloud Architecture Earned Oct 10, 2020 EDT
設定 Google Cloud 網路 Earned Oct 8, 2020 EDT
基本概念:基礎架構 Earned Sep 28, 2020 EDT
建立 Google Cloud 網路 Earned Sep 28, 2020 EDT
雲端工程 Earned Sep 28, 2020 EDT
在 Google Cloud 設定應用程式開發環境 Earned Sep 28, 2020 EDT
在 Compute Engine 導入 Cloud Load Balancing Earned Sep 28, 2020 EDT
Machine Learning APIs Earned Oct 31, 2019 EDT
Intermediate ML: TensorFlow on Google Cloud Earned Oct 30, 2019 EDT
使用 BigQuery 進行機器學習 Earned Oct 28, 2019 EDT
Intro to ML: Image Processing Earned Oct 27, 2019 EDT
基本概念:資料、機器學習和 AI Earned Oct 26, 2019 EDT
Google Cloud Essentials Earned Aug 14, 2019 EDT

Earn a skill badge by completing the Explore Machine Learning Models with Explainable AI quest, where you will learn how to do the following using Explainable AI: build and deploy a model to an AI platform for serving (prediction), use the What-If Tool with an image recognition model, identify bias in mortgage data using the What-If Tool, and compare models using the What-If Tool to identify potential bias. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest and the final assessment challenge lab to receive a skill badge that you can share with your network.

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完成「在 Google Cloud 使用機器學習 API」課程,即可獲得進階技能徽章。本課程說明以下機器學習和 AI 技術的基本功能: Cloud Vision API、Cloud Translation API 和 Cloud Natural Language API。

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完成使用 BigQuery ML 為預測模型進行資料工程技能徽章中階課程, 即可證明自己具備下列知識與技能:運用 Dataprep by Trifacta 建構連至 BigQuery 的資料轉換 pipeline; 使用 Cloud Storage、Dataflow 和 BigQuery 建構「擷取、轉換及載入」(ETL) 工作負載, 以及使用 BigQuery ML 建構機器學習模型。

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完成 從 BigQuery 資料取得深入分析結果 技能徽章入門課程,即可證明您具備下列技能: 撰寫 SQL 查詢、查詢公開資料表、將樣本資料載入 BigQuery、使用 BigQuery 的查詢驗證工具 排解常見語法錯誤,以及在 Looker Studio 中 透過連結 BigQuery 資料建立報表。

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完成「建構安全的 Google Cloud 網路」課程,即可獲得技能徽章。本課程將說明多項網路相關 資源,協助您在 Google Cloud 建構、調度資源和保護應用程式。

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Networking is a principle theme of cloud computing. It’s the underlying structure of Google Cloud, and it’s what connects all your resources and services to one another. This course will cover essential Google Cloud networking services and will give you hands-on practice with specialized tools for developing mature networks. From learning the ins-and-outs of VPCs, to creating enterprise-grade load balancers, Automate Deployment and Manage Traffic on a Google Cloud Network will give you the practical experience needed so you can start building robust networks right away.

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完成 在 Google Cloud 為機器學習 API 準備資料 技能徽章入門課程,即可證明您具備下列技能: 使用 Dataprep by Trifacta 清理資料、在 Dataflow 執行資料管道、在 Dataproc 建立叢集和執行 Apache Spark 工作,以及呼叫機器學習 API,包含 Cloud Natural Language API、Google Cloud Speech-to-Text API 和 Video Intelligence API。

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完成 在 Google Cloud 部署 Kubernetes 應用程式 技能徽章中階課程,即可證明您具備下列技能: 設定及建構 Docker 容器映像檔、建立及管理 Google Kubernetes Engine (GKE) 叢集、運用 kubectl 有效 管理叢集,以及運用強大的持續推送軟體更新做法來部署 Kubernetes 應用程式。

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Kubernetes 是最受歡迎的容器自動化調度管理系統,Google Kubernetes Engine 則專門支援 Google Cloud 中的 代管 Kubernetes 部署項目。這門進階課程將帶您實際練習設定 Docker 映像檔和容器,並部署完整的 Kubernetes Engine 應用程式。 您會學到如何將容器自動化調度管理機制, 整合到自己的工作流程,這些技巧相當實用。 想透過實作挑戰實驗室展現 技能、驗收學習成果嗎?本課程結束後,再完成 在 Google Cloud 部署 Kubernetes 應用程式課程 結尾的挑戰實驗室,即可獲得專屬 Google Cloud 數位徽章。

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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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完成「設定 Google Cloud 網路」課程,即可獲得技能徽章。 您將瞭解如何在 Google Cloud Platform 執行基本的網路工作,包括建立自訂網路、新增子網路防火牆規則,還有建立 VM 並測試 VM 之間的通訊延遲。

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如果您是剛起步的雲端開發人員, 想在 Google Cloud Essentials 外獲得更多實作經驗,歡迎參加本課程。您將透過實作實驗室, 深入瞭解 Cloud Storage 和其他重要應用程式服務,例如: Monitoring 和 Cloud Functions。您將習得 在任何 Google Cloud 專案都適用的寶貴技能。

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完成 建立 Google Cloud 網路 課程即可獲得技能徽章。這個課程將說明 部署及監控應用程式的多種方法,包括查看 IAM 角色及新增/移除 專案存取權、建立虛擬私有雲網路、部署及監控 Compute Engine VM、編寫 SQL 查詢、在 Compute Engine 部署及監控 VM,以及 使用 Kubernetes 透過多種方法部署應用程式。

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本入門課程有別於其他課程。 透過這些實驗室,IT 專業人員將有機會實際練習, 熟悉出現在 Google Cloud 助理雲端工程師認證中的主題和服務。本課程包含多個專門的實驗室,從 IAM、網路建立 到 Kubernetes Engine 部署作業, 可全面驗收您的 Google Cloud 知識。請注意,雖然進行這些 實驗室可提升您的技能和能力,但仍建議同時詳閱 測驗指南和其他可用的準備資源。

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只要修完「在 Google Cloud 設定應用程式開發環境」課程,就能獲得技能徽章。 在本課程中,您將學會如何使用以下技術的基本功能,建構和連結以儲存空間為中心的雲端基礎架構:Cloud Storage、Identity and Access Management、Cloud Functions 和 Pub/Sub。

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完成「在 Compute Engine 導入 Cloud Load Balancing」技能徽章入門課程,即可證明您具備下列技能: 在 Compute Engine 建立及部署虛擬機器, 以及設定網路和應用程式負載平衡器。

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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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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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不想花費大把時間,想在幾分鐘內只靠 SQL,就建立好機器學習模型嗎?透過 BigQuery ML,資料分析師可以運用現有的 SQL 工具和技巧,建立、訓練、評估模型, 並使用模型進行預測,降低機器學習的使用門檻。在 本系列的實驗室,您會測試不同類型的模型,瞭解 優良模型應具備的條件。

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Using large scale computing power to recognize patterns and "read" images is one of the foundational technologies in AI, from self-driving cars to facial recognition. The Google Cloud Platform provides world class speed and accuracy via systems that can utilized by simply calling APIs. With these and a host of other APIs, GCP has a tool for just about any machine learning job. In this introductory quest, you will get hands-on practice with machine learning as it applies to image processing by taking labs that will enable you to label images, detect faces and landmarks, as well as extract, analyze, and translate text from within images.

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大數據、機器學習和人工智慧 (AI) 是時下熱門的 電腦相關話題,但這些領域相當專業,就算想要入門 也難以取得教材或資料。幸好,Google Cloud 提供了此領域的多種服務,而且容易使用。 參加這堂入門課程,您就能踏出第一步, 開始學習運用 BigQuery、Cloud Speech API 以及 Video Intelligence 等工具。

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In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.

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