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VIJAY KUMAR GANAPATHY NAGARAJAN

成为会员时间:2020

注意力机制 Earned Jan 28, 2024 EST
图像生成简介 Earned Jan 22, 2024 EST
Responsible AI: 和 Google Cloud 一起践行 AI 原则 Earned Jan 20, 2024 EST
Generative AI Fundamentals - 简体中文 Earned Jan 20, 2024 EST
负责任的 AI 简介 Earned Jan 20, 2024 EST
大型语言模型简介 Earned Jan 18, 2024 EST
生成式 AI 简介 Earned Jan 18, 2024 EST
Developing Applications with Cloud Run on Google Cloud: Fundamentals Earned Jan 1, 2024 EST
Developing Containerized Applications on Google Cloud Earned Jan 1, 2024 EST
App Deployment, Debugging, and Performance Earned Dec 23, 2023 EST
Securing and Integrating Components of your Application Earned Dec 12, 2023 EST
Getting Started With Application Development Earned Oct 10, 2023 EDT
Google Cloud 基础知识:核心基础设施 Earned Sep 24, 2023 EDT

本课程将向您介绍注意力机制,这是一种强大的技术,可令神经网络专注于输入序列的特定部分。您将了解注意力的工作原理,以及如何使用它来提高各种机器学习任务的性能,包括机器翻译、文本摘要和问题解答。

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本课程向您介绍扩散模型。这类机器学习模型最近在图像生成领域展现出了巨大潜力。扩散模型的灵感来源于物理学,特别是热力学。过去几年内,扩散模型成为热门研究主题并在整个行业开始流行。Google Cloud 上许多先进的图像生成模型和工具都是以扩散模型为基础构建的。本课程向您介绍扩散模型背后的理论,以及如何在 Vertex AI 上训练和部署此类模型。

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随着企业对人工智能和机器学习的应用越来越广泛,以负责任的方式构建这些技术也变得更加重要。但对很多企业而言,真正践行 Responsible AI 并非易事。如果您有意了解如何在组织内践行 Responsible AI,本课程正适合您。 本课程将介绍 Google Cloud 目前如何践行 Responsible AI,以及从中总结的最佳实践和经验教训,便于您以此为框架构建自己的 Responsible AI 方法。

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完成 Introduction to Generative AI、Introduction to Large Language Models 和 Introduction to Responsible AI 三门课程,赢取技能徽章。通过最终测验,即表明您理解了生成式 AI 的基本概念。 技能徽章是由 Google Cloud 颁发的数字徽章,旨在认可您对 Google Cloud 产品与服务的了解程度。公开您的个人资料并将技能徽章添加到您的社交媒体个人资料中,以此来分享您获得的成就。

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这是一节入门级微课程,旨在解释什么是负责任的 AI、它的重要性,以及 Google 如何在自己的产品中实现负责任的 AI。此外,本课程还介绍了 Google 的 7 个 AI 开发原则。

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这是一节入门级微学习课程,探讨什么是大型语言模型 (LLM)、适合的应用场景以及如何使用提示调整来提升 LLM 性能,还介绍了可以帮助您开发自己的 Gen AI 应用的各种 Google 工具。

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这是一节入门级微课程,旨在解释什么是生成式 AI、它的用途以及与传统机器学习方法的区别。该课程还介绍了可以帮助您开发自己的生成式 AI 应用的各种 Google 工具。

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This course introduces the Cloud Run serverless platform for running applications. In this course, you learn about the fundamentals of Cloud Run, its resource model and the container lifecycle. You learn about service identities, how to control access to services, and how to develop and test your application locally before deploying it to Cloud Run. The course also teaches you how to integrate with other services on Google Cloud so you can build full-featured applications.

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In this course, you learn about containers and how to build, and package container images. The content in this course includes best practices for creating and securing containers, and provides an introduction to Cloud Run and Google Kubernetes Engine for application developers.

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In this course, application developers learn how to design and develop cloud-native applications that seamlessly integrate components from the Google Cloud ecosystem. Through a combination of presentations, demos, and hands-on labs, participants learn how to create repeatable deployments by treating infrastructure as code, choose the appropriate application execution environment for an application, and monitor application performance. Completing one version of each lab is required. Each lab is available in Node.js. In most cases, the same labs are also provided in Python or Java. You may complete each lab in whichever language you prefer.

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In this course, application developers learn how to design and develop cloud-native applications that seamlessly integrate managed services from Google Cloud. Through a combination of presentations, demos, and hands-on labs, participants learn how to develop more secure applications, implement federated identity management, and integrate application components by using messaging, event-driven processing, and API gateways. Completing one version of each lab is required. Each lab is available in Node.js. In most cases, the same labs are also provided in Python or Java. You may complete each lab in whichever language you prefer. This is the second course of the Developing Applications with Google Cloud series. After completing this course, enroll in the App Deployment, Debugging, and Performance course.

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In this course, application developers learn how to design and develop cloud-native applications that seamlessly integrate managed services from Google Cloud. Through a combination of presentations, demos, and hands-on labs, participants learn how to apply best practices for application development and use the appropriate Google Cloud storage services for object storage, relational data, caching, and analytics. Completing one version of each lab is required. Each lab is available in Node.js. In most cases, the same labs are also provided in Python or Java. You may complete each lab in whichever language you prefer. This is the first course of the Developing Applications with Google Cloud series. After completing this course, enroll in the Securing and Integrating Components of your Application course.

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“Google Cloud 基础知识:核心基础设施”介绍在使用 Google Cloud 时会遇到的重要概念和术语。本课程通过视频和实操实验来介绍并比较 Google Cloud 的多种计算和存储服务,并提供重要的资源和政策管理工具。

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