Syed Hamza Hussain
成为会员时间:2020
白银联赛
10885 积分
成为会员时间:2020
探索生成式 AI - Agent Platform”课程包含一系列实验, 指导用户在 Google Cloud 平台上使用生成式 AI。通过这些实验,您将了解 如何在 Agent Platform 中使用 Gemini 模型。您还将了解提示设计、最佳实践, 以及如何使用生成式 AI 进行构思、文本分类、文本提取、文本摘要等。此外, 您将学习如何通过 Agent Platform 中的自定义训练来训练基础模型, 从而对其进行调优,以及如何将其部署到 Agent Platform 中的端点。
各种规模的组织都在利用云的强大功能和灵活性来改变运营方式。然而,有效管理和扩缩云资源可能是一项复杂的任务。本课程探讨了云中现代运营、可靠性和弹性方面的基本概念,以及 Google Cloud 如何帮助支持这些工作。 作为 Cloud Digital Leader 学习路线的一部分,本课程旨在帮助个人在自己的岗位上成长,并为企业谋求未来发展。
许多传统企业都在使用无法满足现代客户期望的旧式系统和应用。业务领导者往往需要在维护老旧的 IT 系统和投资新产品与服务之间做出选择。本课程探讨了这些挑战,并提供了利用云技术克服这些挑战的解决方案。 作为 Cloud Digital Leader 学习路线的一部分,本课程旨在帮助个人在工作中成长,并为企业打造美好未来。
云技术是一项强大的资产,与数据相结合后,它将成为创新和提升客户体验的催化剂。《使用 Google Cloud 探索数据转换》课程探讨了组织如何利用云技术让数据更易于访问、更具实用价值和商业价值。 作为“Cloud Digital Leader 学习路线”的一部分,本课程旨在帮助个人提升职业素养,并为企业谋求未来发展。
数字化转型是现代组织的必经之路,而扎实掌握云计算基础知识,是推动实质性创新的第一步。《利用 Google Cloud 实现数字化转型》课程将讲解核心技术与战略框架,助力组织实现运营现代化。本课程介绍关于云的基本概念、全球网络基础设施和责任共担模式,帮助领导者从容推进上云进程。 作为 Cloud Digital Leader 学习路线的一部分,本课程旨在帮助学员提升岗位能力,从而为企业打造美好未来。
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。
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。
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。
完成入门级技能徽章课程在 Google Cloud 上为机器学习 API 准备数据,展示以下技能: 使用 Dataprep by Trifacta 清理数据、在 Dataflow 中运行数据流水线、在 Managed Service for Apache Spark 中创建集群和运行 Apache Spark 作业,以及调用机器学习 API,包括 Cloud Natural Language API、Google Cloud Speech-to-Text API 和 Video Intelligence API。
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.
完成在 Google Cloud 上使用 Machine Learning API 课程,赢取高级技能徽章。 在本课程中,您将了解以下机器学习和 AI 技术的基本功能: Cloud Vision API、Cloud Translation API 和 Cloud Natural Language API。
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.
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.
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.
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.
众所周知,机器学习是发展最快的技术领域之一, Google Cloud Platform 在推动其发展方面发挥了重要作用。 GCP 提供了一系列 API,几乎可以满足任何机器学习作业的需求。在 本入门课程中,您将了解机器学习在语言处理方面的运用, 通过实操实验学习 如何从文本中提取实体,执行情感和语法分析,以及 使用 Speech-to-Text API 进行转写。
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.