Mohtashim Khan
Member since 2017
Silver League
1600 points
Member since 2017
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。
This introductory-level quest shows application developers how the Google Cloud ecosystem could help them build secure, scalable, and intelligent cloud native applications. You learn how to develop and scale applications without setting up infrastructure, run data analytics, gain insights from data, and develop with pre-trained ML APIs to leverage machine learning even if you are not a Machine Learning expert. You will also experience seamless integration between various Google services and APIs to create intelligent apps.
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.
透過 DevOps 取得 競爭優勢。DevOps 作業涵蓋組織與文化層面,目標為加速推送軟體、 提高服務穩定性,並為所有軟體相關人員 建立共同擁有權。這堂課程說明如何使用 Google Cloud 提高軟體推送功能的速度、穩定性、可用性和安全性。 開發運作研究與評估計畫已新增至 Google Cloud。想知道自己的團隊表現如何嗎?完成 這個五道選擇題的測驗就能知道答案!
在這堂入門課程,您將實際練習使用 Google Cloud 的基礎工具和服務。本課程包含可選擇觀賞的影片, 針對實驗室涵蓋的概念提供更多背景資訊,協助您複習。「Google Cloud 必備知識」 是適合 Google Cloud 學員的第一堂課, 即使您尚未學習或不熟悉雲端知識, 也能從這堂課獲得實務經驗,並應用於第一項 Google Cloud 專案。不管是撰寫 Cloud Shell 指令 和部署第一部虛擬機器,還是在 Kubernetes Engine 或透過負載平衡執行應用程式, 「Google Cloud 必備知識」都是認識平台基本功能的最佳入門資源。