Getting Started with Go on Google Cloud
Earned Feb 25, 2021 EST
Data Science on Google Cloud
Earned Feb 25, 2021 EST
DEPRECATED Application Development - Python
Earned Feb 24, 2021 EST
Machine Learning APIs
Earned Feb 23, 2021 EST
机器学习简介：语言处理
Earned Feb 22, 2021 EST
DEPRECATED Explore Machine Learning Models with Explainable AI
Earned Feb 19, 2021 EST
在 Google Cloud 上使用 Machine Learning API
Earned Feb 18, 2021 EST
通过 BigQuery ML 创建机器学习模型
Earned Feb 16, 2021 EST
DEPRECATED BigQuery Basics for Data Analysts
Earned Feb 13, 2021 EST
从 BigQuery 数据中挖掘数据洞见
Earned Feb 13, 2021 EST
在 Google Cloud 上为机器学习 API 准备数据
Earned Feb 9, 2021 EST
开发 Google Cloud 网络
Earned Feb 6, 2021 EST
在 Google Cloud 上设置应用开发环境
Earned Feb 3, 2021 EST
为 Compute Engine 实现云负载均衡
Earned Jan 29, 2021 EST
Get started with Go (Golang) by reviewing Go code, and then creating and deploying simple Go apps on Google Cloud. Go is an open source programming language that makes it easy to build fast, reliable, and efficient software at scale. Go runs native on Google Cloud, and is fully supported on Google Kubernetes Engine, Compute Engine, App Engine, Cloud Run, and Cloud Functions. Go is a compiled language and is faster and more efficient than interpreted languages. As a result, Go requires no installed runtime like Node, Python, or JDK to execute.
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This is the first of two Quests of hands-on labs is derived from the exercises from the book Data Science on Google Cloud Platform, 2nd Edition by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this first Quest, covering up through chapter 8, you are given the opportunity to practice all aspects of ingestion, preparation, processing, querying, exploring and visualizing data sets using Google Cloud tools and services.
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In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Python. 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 Python 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 Python applications straight away.
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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.
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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。
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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 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。
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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。
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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.
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 Dataproc 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。
Getting Started with Go on Google Cloud
Earned Feb 25, 2021 EST
Data Science on Google Cloud
Earned Feb 25, 2021 EST
DEPRECATED Application Development - Python
Earned Feb 24, 2021 EST
Machine Learning APIs
Earned Feb 23, 2021 EST
机器学习简介：语言处理
Earned Feb 22, 2021 EST
DEPRECATED Explore Machine Learning Models with Explainable AI
Earned Feb 19, 2021 EST
在 Google Cloud 上使用 Machine Learning API
Earned Feb 18, 2021 EST
通过 BigQuery ML 创建机器学习模型
Earned Feb 16, 2021 EST
DEPRECATED BigQuery Basics for Data Analysts
Earned Feb 13, 2021 EST
从 BigQuery 数据中挖掘数据洞见
Earned Feb 13, 2021 EST
在 Google Cloud 上为机器学习 API 准备数据
Earned Feb 9, 2021 EST
开发 Google Cloud 网络
Earned Feb 6, 2021 EST
在 Google Cloud 上设置应用开发环境
Earned Feb 3, 2021 EST
为 Compute Engine 实现云负载均衡
Earned Jan 29, 2021 EST