Ibrahim Zakaria
成为会员时间:2021
青铜联赛
3900 积分
成为会员时间:2021
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。
完成中级技能徽章课程通过 BigQuery ML 创建机器学习模型,展示您在以下方面的技能: 使用 BigQuery ML 创建和评估机器学习模型,以执行数据预测。
When it comes to hosting websites and web applications, you want a framework that’s robust, fast, and secure. By choosing the Google Cloud Platform, you will have all of those needs covered. In this fundamental-level quest, you will get hands-on practice with GCPs key infrastructure and computing services for the web. From deploying your first web app, to integrating Cloud SQL with Ruby on Rails, to mapping the NYC subway system on App Engine, you will learn all the skills needed to harness GCPs web hosting power.
Google Cloud is committed to supporting Windows workloads in its frameworks and services. In this quest, you will get hands-on practice running Microsoft’s ASP.net (web app framework) on Google Cloud. ASP.NET is an open-source and cross-platform framework for building modern cloud-based and internet-connected applications using the C# programming language.
Google Cloud Application Programming Interfaces are the mechanism to interact with Google Cloud Services programmatically. This quest will give you hands-on practice with a variety of GCP APIs, which you will learn through working with Google’s APIs Explorer, a tool that allows you to browse APIs and run their methods interactively. By learning how to transfer data between Cloud Storage buckets, deploy Compute Engine instances, configure Dataproc clusters and much more, Exploring APIs will show you how powerful APIs are and why they are used almost exclusively by proficient GCP users. Enroll in this quest today.
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。
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.
在本入门级课程中,您将了解 Google Cloud 的基础工具和服务。此课程提供了可选视频, 旨在帮助您深入了解和回顾实验中涉及的概念。Google Cloud 基础知识是推荐给 Google Cloud 学员的第一门课程 - 即使您几乎没有云相关知识,也能从中获得实践 经验,并将其直接运用于您的首个 Google Cloud 项目。从编写 Cloud Shell 命令和部署您的第一个虚拟机,到在 Kubernetes Engine 上运行应用 或者使用负载均衡,“Google Cloud 基础知识”都是您了解该平台 基本功能的首选入门级课程。
Workspace 是 Google 的协作应用 平台,由 Google Cloud 提供。在本入门级课程中,您将 从用户角度对 Workspace 的核心应用进行实操练习。虽然 Workspace 包含的应用和工具组件远多于本课程涵盖的范围, 但您将实际操作主要应用:Gmail、日历、表格以及 以及其他一些应用。每个实验可在 10–15 分钟内完成,但课程预留了额外 时间,供您自主自由探索这些应用。
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.
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.
想要仅使用 SQL 就能在几分钟内构建机器学习模型,而不是花费数小时?BigQuery 借助机器学习,数据分析师能够使用现有的 SQL 工具和技能创建、训练、评估机器学习模型,并使用这些模型进行预测, 从而实现机器学习的普及。在 本系列实验中,您将尝试不同的模型类型,并了解 如何构建出色的模型。
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.
Google Cloud is committed to supporting Windows workloads in its frameworks and services. In this advanced-level quest, you will get hands-on practice running many of the popular Windows services on Google Cloud. For example, you will learn how to instantiate Microsoft SQL databases, cloud tools for Powershell on Google Cloud Platform frameworks.
In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Java. 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 Java 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 Java applications straight away.
Firebase is a backend-as-service (Bass) platform for creating mobile and web applications. In this quest you will learn to build serverless web apps, import data into a serverless database, and build a Google Assistant application with Firebase and its Google Cloud integrations. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.
Earn a skill badge by completing the Build Interactive Apps with Google Assistant quest, where you will learn how to build Google Assistant applications, including how to: create an Actions project, integrate Dialogflow with an Actions project, test your application with Actions simulator, build an Assistant application with flash cards template, integrate customer MP3 files with your Assistant application, add Cloud Translation API to your Assistant application, and use APIs and integrate them into your applications. 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 the skill badge quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.
The Google Cloud Platform provides many different frameworks and options to fit your application’s needs. In this introductory-level quest, you will get plenty of hands-on practice deploying sample applications on Google App Engine. You will also dive into other web application frameworks like Firebase, Wordpress, and Node.js and see firsthand how they can be integrated with Google Cloud.