Just For My Daily Diary
Just For My Daily Diary
Introduction 简介 One of the most basic questions we might ask of a model is: What features have the biggest impact on predictions? 我们可能会问模型的一个最基本问题是：哪些特征对预测的影响最大？ This concept is called feature importance. 这个概念称为特征重要性。 There are multiple ways to measure feature importance. Some approaches answer subtly different versions of the question above. Other approaches have documented shortcomings. 有多种方法来衡量特征重要性。一些方法回答了上述问题的微妙不同版本。其他方法有记录的缺点。 […]
What Types of Insights Are Possible 可能获得哪些类型的洞察 Many people say machine learning models are "black boxes", in the sense that they can make good predictions but you can’t understand the logic behind those predictions. This statement is true in the sense that most data scientists don’t know how to extract insights from models yet. 许多人说机器学习模型是“黑匣子”，即它们可以做出正确的预测，但你无法理解这些预测背后的逻辑。这种说法是正确的，因为大多数数据科学家还不知道如何从模型中提取洞察。 […]
This notebook is an exercise in the AI Ethics course. You can reference the tutorial at this link. In the tutorial, you learned how to use model cards. In this exercise, you’ll sharpen your understanding of model cards by engaging with them in a couple of scenarios. 在本教程中，您学习了如何使用模型卡。在本练习中，您将通过在几个场景中使用模型卡来加深对模型卡的理解。 Introduction 简介 Run the next code cell […]
Introduction 简介 A model card is a short document that provides key information about a machine learning model. Model cards increase transparency by communicating information about trained models to broad audiences. 模型卡 是一份简短的文档，提供有关机器学习模型的关键信息。模型卡通过向广大受众传达有关训练模型的信息来提高透明度。 In this tutorial, you will learn about which audiences to write a model card for and which sections a model card should […]
This notebook is an exercise in the AI Ethics course. You can reference the tutorial at this link. In the tutorial, you learned about different ways of measuring fairness of a machine learning model. In this exercise, you’ll train a few models to approve (or deny) credit card applications and analyze fairness. Don’t worry if […]
Introduction 简介 There are many different ways of defining what we might look for in a fair machine learning (ML) model. For instance, say we’re working with a model that approves (or denies) credit card applications. Is it: 定义公平机器学习 (ML) 模型中我们可能寻找的内容有很多不同的方法。例如，假设我们正在使用一个批准（或拒绝）信用卡申请的模型。它是： fair if the approval rate is equal across genders, or is it 如果批准率在性别之间相等，是否公平，或者 better […]
This notebook is an exercise in the AI Ethics course. You can reference the tutorial at this link. In the tutorial, you learned about six different types of bias. In this exercise, you’ll train a model with real data and get practice with identifying bias. Don’t worry if you’re new to coding: you’ll still be […]
Introduction 简介 Machine learning (ML) has the potential to improve lives, but it can also be a source of harm. ML applications have discriminated against individuals on the basis of race, sex, religion, socioeconomic status, and other categories. 机器学习 (ML) 有可能改善生活，但也可能造成伤害。ML 应用程序会根据种族、性别、宗教、社会经济地位和其他类别歧视个人。 In this tutorial, you’ll learn about bias, which refers to negative, unwanted consequences […]
This notebook is an exercise in the AI Ethics course. You can reference the tutorial at this link. In the tutorial, you learned about human-centered design (HCD) and became familiar with six general steps to apply it to AI systems. In this exercise, you will identify and address design issues in six interesting AI use […]
Introduction 简介 Before selecting data and training models, it is important to carefully consider the human needs an AI system should serve – and if it should be built at all. 在选择数据和训练模型之前，重要的是要仔细考虑 AI 系统应该满足的人类需求 – 以及是否应该构建它。 Human-centered design (HCD) is an approach to designing systems that serve people’s needs. 以人为本的设计 (HCD) 是一种设计满足人们需求的系统的方法。 In this tutorial, […]