引导式测验 · 中等 等级

模型注册测验

应用模型注册表版本、签名和部署引用，包括为什么别名更改需要经过验证的服务工作流程。

相关引导路径模型注册表
问题 1 的 8

模型注册表的主要目的是什么？

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  1. 模型注册表的主要目的是什么？
    • 标记原始训练数据
    • 充当经过训练的模型的版本控制目录和单一事实来源
    • 更换服务器中的 GPU
    • 编写 SQL 查询
  2. In current MLflow registry workflows, what can provide a named reference to a model version?
    • A reassignable model alias
    • A universal mandatory four-stage lifecycle in every registry
    • The training GPU’s display resolution
    • A random tensor without a model version
  3. How can a registry support a model rollback?
    • By guaranteeing every server switches instantly
    • By deleting all previous versions
    • By retaining a previous artifact that the serving workflow can reload and validate
    • By changing the training labels automatically
  4. 什么是注册表中的模型签名？
    • 数据科学家的手写亲笔签名
    • 数据库的密码
    • 模型的训练时长
    • 描述模型预期输入和输出类型的模式
  5. 为什么记录的谱系（数据集、代码提交、超参数）很有价值？
    • 它实现了每个版本的构建方式的可重复性和可审核性
    • 它使模型运行得更快
    • 它自动提高模型的准确性
    • 它压缩模型文件
  6. What connects a registered model decision to an actual application rollout?
    • A guarantee that registering a version deploys it everywhere
    • A required fax to the GPU vendor
    • A configured deployment workflow that loads and verifies the chosen artifact
    • A model signature alone with no serving system
  7. A champion alias is reassigned, but a long-running server still has the old artifact loaded. What should an operator verify?
    • Only that the alias has a new value
    • That all servers reload automatically in every integration
    • Only the number of files in the registry
    • The artifact and version actually serving requests
  8. A model signature expects numerical columns but a request sends strings. What can signature-aware validation help detect?
    • Whether the training labels are morally correct
    • An input schema or type mismatch
    • Every possible accuracy regression
    • A guarantee that all numerical inputs are in distribution