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 […]
This notebook is an exercise in the Data Cleaning course. You can reference the tutorial at this link. In this exercise, you’ll apply what you learned in the Inconsistent data entry tutorial. 在本练习中，您将应用在数据不一致教程中学到的知识。 Setup 设置 The questions below will give you feedback on your work. Run the following cell to set up the feedback system. […]
In this notebook, we’re going to learn how to clean up inconsistent text entries. 在本笔记本中，我们将学习如何清理不一致的文本条目。 Let’s get started! 让我们开始吧！ Get our environment set up 设置我们的环境 The first thing we’ll need to do is load in the libraries and dataset we’ll be using. 我们需要做的第一件事是加载我们将使用的库和数据集。 # pip install fuzzywuzzy, python-Levenshtein # modules we'll use import pandas as […]
This notebook is an exercise in the Data Cleaning course. You can reference the tutorial at this link. In this exercise, you’ll apply what you learned in the Character encodings tutorial. 在本练习中，您将应用在 字符编码 教程中所学到的知识。 Setup 设置 The questions below will give you feedback on your work. Run the following cell to set up the feedback […]
In this notebook, we’re going to be working with different character encodings. 在本笔记本中，我们将使用不同的字符编码。 Let’s get started! 让我们开始吧！ Get our environment set up 设置我们的环境 The first thing we’ll need to do is load in the libraries we’ll be using. Not our dataset, though: we’ll get to it later! 我们需要做的第一件事是加载我们将使用的库。 不过，这不是我们的数据集：我们稍后会处理它！ # modules we'll use import pandas […]
Time-series plotting (Optional) 时间序列绘图（可选） In all of the sections thus far our visualizations have focused on and used numeric variables: either categorical variables, which fall into a set of buckets, or interval variables, which fall into an interval of values. In this notebook we will explore another type of variable: a time-series variable. 到目前为止，在所有部分中，我们的可视化都集中在并使用了数字变量：要么是属于一组用桶(buckets)存储的 calcategories […]
This notebook is an exercise in the Data Cleaning course. You can reference the tutorial at this link. In this exercise, you’ll apply what you learned in the Parsing dates tutorial. 在本练习中，您将应用在 解析日期 教程中学到的知识。 Setup 设置 The questions below will give you feedback on your work. Run the following cell to set up the feedback […]
In this notebook, we’re going to work with dates. 在此笔记本中，我们将处理日期。 Let’s get started! 让我们开始吧！ Get our environment set up 设置我们的环境 The first thing we’ll need to do is load in the libraries and dataset we’ll be using. We’ll be working with a dataset that contains information on landslides that occured between 2007 and 2016. In […]