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Syed Hamza Hussain

Member since 2020

Silver League

10885 points
探索生成式 AI - Agent Platform Earned Jan 25, 2025 EST
使用 Google Cloud 作業套件調度資源 Earned Nov 18, 2023 EST
運用 Google Cloud 翻新基礎架構和應用程式 Earned Nov 18, 2023 EST
運用 Google Cloud 探索資料轉換功能 Earned Nov 18, 2023 EST
透過 Google Cloud 進行數位轉型 Earned Nov 18, 2023 EST
負責任的 AI 技術簡介 Earned Nov 18, 2023 EST
生成式 AI 簡介 Earned Nov 18, 2023 EST
大型語言模型簡介 Earned Nov 18, 2023 EST
在 Google Cloud 為機器學習 API 準備資料 Earned Oct 10, 2020 EDT
DEPRECATED Explore Machine Learning Models with Explainable AI Earned Oct 10, 2020 EDT
在 Google Cloud 使用機器學習 API Earned Oct 9, 2020 EDT
Intermediate ML: TensorFlow on Google Cloud Earned Oct 8, 2020 EDT
NCAA® March Madness®: Bracketology with Google Cloud Earned Oct 7, 2020 EDT
DEPRECATED BigQuery for Marketing Analysts Earned Oct 7, 2020 EDT
DEPRECATED BigQuery Basics for Data Analysts Earned Oct 7, 2020 EDT
機器學習簡介:語言處理 Earned Oct 5, 2020 EDT
Intro to ML: Image Processing Earned Oct 4, 2020 EDT

「探索生成式 AI - Agent Platform」課程包含一系列實驗室, 介紹如何在 Google Cloud 使用生成式 AI。完成這些實驗室之後,您會瞭解如何 在 Agent Platform 使用 Gemini 模型、提示詞設計技巧與最佳做法,以及 AI 在構思想法和文字分類、擷取、摘要等方面的用途。您也會瞭解如何運用 Agent Platform 的自訂訓練功能調整基礎模型, 並部署至 Agent Platform 中的端點。

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各種規模的機構都開始運用雲端的強大功能和靈活性,徹底改變營運方式。不過,有效管理及擴充雲端資源可能是相當複雜的工作。本課程將探討在雲端中的現代營運、可靠性和韌性的基礎概念,以及 Google Cloud 如何協助您達成這些目標。本課程是 Cloud Digital Leader 學習路徑的一部分,旨在促進個人職能發展,並打造企業的未來。

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許多傳統企業使用舊版系統和應用程式,無法滿足現今客戶的期望。企業主管經常需要在維護老舊的 IT 系統,以及投資新產品/服務之間做出選擇。本課程將探討這些挑戰,並提供解決方案,說明如何運用雲端技術克服難題。 本課程是 Cloud Digital Leader 學習路徑的一部分,旨在促進個人職能發展,並打造企業的未來。

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雲端技術是強大的資產,與資料搭配後,將成為創新和提升客戶體驗的催化劑。「運用 Google Cloud 探索資料轉換功能」課程將探討機構如何運用雲端,讓資料更易於存取、做為行動依據和更有價值。 這門課程是 Cloud Digital Leader 學習路徑的一部分,旨在協助個人在職務上成長,並打造企業的未來。

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數位轉型是現代組織必經的關鍵旅程,而建立穩固的雲端運算基礎,是跨出有意義創新的第一步。本課程「透過 Google Cloud 進行數位轉型」,將會介紹核心技術和策略框架,協助組織革新營運方式,並探討基本的雲端概念、全球網路基礎架構和共同責任模式,幫助主管在雲端之路上自信前行。本課程是 Cloud Digital Leader 學習路徑的一部分,旨在促進個人職能發展,並打造企業的未來。

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這個入門微學習課程主要介紹「負責任的 AI 技術」和其重要性,以及 Google 如何在自家產品中導入這項技術。本課程也會說明 Google 的 7 個 AI 開發原則。

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這個入門微學習課程主要說明生成式 AI 的定義和使用方式,以及此 AI 與傳統機器學習方法的差異。本課程也會介紹各項 Google 工具,協助您開發自己的生成式 AI 應用程式。

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這是一堂入門級的微學習課程,旨在探討大型語言模型 (LLM) 的定義和用途,並說明如何調整提示來提高 LLM 成效。此外,也會介紹多項 Google 工具,協助您自行開發生成式 AI 應用程式。

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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 Managed Service for Apache Spark 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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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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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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In this series of labs you will learn how to use BigQuery to analyze NCAA basketball data with SQL. Build a Machine Learning Model to predict the outcomes of NCAA March Madness basketball tournament games.

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Want to turn your marketing data into insights and build dashboards? Bring all of your data into one place for large-scale analysis and model building. Get repeatable, scalable, and valuable insights into your data by learning how to query it and using BigQuery. 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.

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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.

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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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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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