Getting Started with Go on Google Cloud
Earned Feb 25, 2021 EST
Data Science on Google Cloud
Earned Feb 25, 2021 EST
DEPRECATED Application Development - Python
Earned Feb 24, 2021 EST
Machine Learning APIs
Earned Feb 23, 2021 EST
機器學習簡介：語言處理
Earned Feb 22, 2021 EST
DEPRECATED Explore Machine Learning Models with Explainable AI
Earned Feb 19, 2021 EST
在 Google Cloud 使用機器學習 API
Earned Feb 18, 2021 EST
運用 BigQuery ML 建立機器學習模型
Earned Feb 16, 2021 EST
DEPRECATED BigQuery Basics for Data Analysts
Earned Feb 13, 2021 EST
從 BigQuery 資料取得深入分析結果
Earned Feb 13, 2021 EST
在 Google Cloud 為機器學習 API 準備資料
Earned Feb 9, 2021 EST
建立 Google Cloud 網路
Earned Feb 6, 2021 EST
在 Google Cloud 設定應用程式開發環境
Earned Feb 3, 2021 EST
在 Compute Engine 導入 Cloud Load Balancing
Earned Jan 29, 2021 EST
Get started with Go (Golang) by reviewing Go code, and then creating and deploying simple Go apps on Google Cloud. Go is an open source programming language that makes it easy to build fast, reliable, and efficient software at scale. Go runs native on Google Cloud, and is fully supported on Google Kubernetes Engine, Compute Engine, App Engine, Cloud Run, and Cloud Functions. Go is a compiled language and is faster and more efficient than interpreted languages. As a result, Go requires no installed runtime like Node, Python, or JDK to execute.
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This is the first of two Quests of hands-on labs is derived from the exercises from the book Data Science on Google Cloud Platform, 2nd Edition by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this first Quest, covering up through chapter 8, you are given the opportunity to practice all aspects of ingestion, preparation, processing, querying, exploring and visualizing data sets using Google Cloud tools and services.
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In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Python. The first labs will walk you through the basics of environment setup and application data storage with Cloud Datastore. Once you have a handle on the fundamentals, you will get hands-on practice deploying Python applications on Kubernetes and App Engine (the latter is the same framework that powers Snapchat!) With specialized bonus labs that teach user authentication and backend service development, this quest will give you practical experience so you can start developing robust Python applications straight away.
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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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大家都知道，機器學習是發展最快的科技領域之一， 而 Google Cloud Platform 在這方面功不可沒。 GCP 提供多種 API，凡是與機器學習相關的任務，幾乎都能處理。您將在本入門課程的 實驗室，實際演練機器學習技術 在語言處理方面的應用，學會如何從文中擷取實體資訊、 執行情緒和語法分析，並使用 Speech-to-Text API 轉錄語音。
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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「運用 BigQuery ML 建立機器學習模型」技能徽章中階課程，即可證明您具備下列技能： 可使用 BigQuery ML 建立及評估機器學習模型，並根據資料進行預測。
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Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
Getting Started with Go on Google Cloud
Earned Feb 25, 2021 EST
Data Science on Google Cloud
Earned Feb 25, 2021 EST
DEPRECATED Application Development - Python
Earned Feb 24, 2021 EST
Machine Learning APIs
Earned Feb 23, 2021 EST
機器學習簡介：語言處理
Earned Feb 22, 2021 EST
DEPRECATED Explore Machine Learning Models with Explainable AI
Earned Feb 19, 2021 EST
在 Google Cloud 使用機器學習 API
Earned Feb 18, 2021 EST
運用 BigQuery ML 建立機器學習模型
Earned Feb 16, 2021 EST
DEPRECATED BigQuery Basics for Data Analysts
Earned Feb 13, 2021 EST
從 BigQuery 資料取得深入分析結果
Earned Feb 13, 2021 EST
在 Google Cloud 為機器學習 API 準備資料
Earned Feb 9, 2021 EST
建立 Google Cloud 網路
Earned Feb 6, 2021 EST
在 Google Cloud 設定應用程式開發環境
Earned Feb 3, 2021 EST
在 Compute Engine 導入 Cloud Load Balancing
Earned Jan 29, 2021 EST