按照您自己的方式探索 Google Cloud 培训。
Google Cloud 提供 700 多项学习活动供您选择,我们设计的目录完整全面,充分考虑了您的需求。该目录包含各种可供您选择的活动形式,既有简短的单个实验,也有由视频、文档、实验和测验组成的多模块课程,您可以根据需求进行选择。我们的实验可为您提供实际云资源的临时凭据,以便您通过实际操作掌握 Google Cloud 知识。您可以跟踪、衡量和了解自己的 Google Cloud 学习进度,完成学习活动即可赢取徽章!
110 条结果
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课程 精选 Launching into Machine Learning
The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a …
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课程 精选 Smart Analytics, Machine Learning, and AI on Google Cloud
Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course…
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课程 精选 Machine Learning Operations (MLOps): Getting Started
This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professiona…
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实验 精选 Machine Learning with TensorFlow in Vertex AI
In this lab you will learn how to use Google Cloud Machine Learning and Tensorflow to develop and evaluate prediction models using machine learning.
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课程 精选 Google Cloud Solutions II: Data and Machine Learning
In this advanced-level quest, you will learn how to harness serious Google Cloud computing power to run big data and machine learning jobs. The hands-on labs will give you use cases, and you will be tasked with implementing big data and machine learning practices utilized by Google’s very own Solutions Architectur…
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课程 精选 Production Machine Learning Systems
This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed t…
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实验 精选 BigQuery Machine Learning using Soccer Data
Learn how to use BigQuery ML with soccer shot data to create and use an expected goals model.
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课程 精选 How Google Does Machine Learning
This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning. You’re introduced to Vertex AI, a unified platform to quickly build, train, and deploy AutoML machine learning models. The course discusses the five phases of converting a …
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课程 精选 Machine Learning in the Enterprise
This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing. The team is presented with three…
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课程 精选 Machine Learning Operations (MLOps) with Vertex AI: Manage Features
This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Learners will get hands-on practice u…