Flashield's Blog

Just For My Daily Diary

Flashield's Blog

Just For My Daily Diary

Python

01.course-what-is-feature-engineering【什么是特征工程】

Welcome to Feature Engineering! 欢迎来到特征工程! In this course you’ll learn about one of the most important steps on the way to building a great machine learning model: feature engineering. You’ll learn how to: 在本课程中,您将了解构建出色的机器学习模型的最重要步骤之一:特征工程。 您将学习如何: determine which features are the most important with mutual information 通过互信息确定哪些特征最重要 invent new features in several real-world problem domains 在几个现实问题领域发明新功能 […]

08.course-creating-your-own-notebooks【创建你自己的笔记本】

Congratulations for making it to the end of the course! 恭喜您来到最后一课! In this final tutorial, you’ll learn an efficient workflow that you can use to continue creating your own stunning data visualizations on the Kaggle website. 在这最后一个教程中,您将学习一个高效的工作流程,您可以使用该工作流程继续在 Kaggle 网站上创建您自己的令人惊叹的数据可视化。 Workflow 工作流 Begin by navigating to the site for Kaggle Notebooks: 首先导航到 Kaggle Notebooks 站点: https://www.kaggle.com/code […]

07.exercise-final-project【练习:最终项目】

This notebook is an exercise in the Data Visualization course. You can reference the tutorial at this link. Now it’s time for you to demonstrate your new skills with a project of your own! 现在是您通过自己的项目展示您的新技能的时候了! In this exercise, you will work with a dataset of your choosing. Once you’ve selected a dataset, you’ll design and […]

07.course-final-project【最终项目】

So far, you have worked with datasets that we have provided for you. In this tutorial, you’ll learn how to use your own datasets. Then, in the following exercise, you’ll design and create your own data visualizations. 到目前为止,您已经使用了我们为您提供的数据集。 在本教程中,您将学习如何使用自己的数据集。 然后,在下面的练习中,您将设计和创建自己的数据可视化。 Kaggle Datasets Kaggle 数据集 You can access Kaggle Datasets by visiting the link below: 您可以通过访问以下链接访问 […]

06.exercise-choosing-plot-types-and-custom-styles【练习:选择图表类型和自定义样式】

This notebook is an exercise in the Data Visualization course. You can reference the tutorial at this link. In this exercise, you’ll explore different chart styles, to see which color combinations and fonts you like best! 在本练习中,您将探索不同的图表样式,看看您最喜欢哪种颜色组合和字体! Setup 设置 Run the next cell to import and configure the Python libraries that you need to complete […]

06.course-choosing-plot-types-and-custom-styles【选择图表类型及自定义样式】

In this course, you’ve learned how to create many different chart types. Now, you’ll organize your knowledge, before learning some quick commands that you can use to change the style of your charts. 在本课程中,您学习了如何创建许多不同的图表类型。 现在,您将整理您的知识,然后学习一些可用于更改图表样式的快速命令。 What have you learned? 你已经学到了什么? Since it’s not always easy to decide how to best tell the story behind your […]

05.exercise-distributions【练习:分布图】

This notebook is an exercise in the Data Visualization course. You can reference the tutorial at this link. In this exercise, you will use your new knowledge to propose a solution to a real-world scenario. To succeed, you will need to import data into Python, answer questions using the data, and generate histograms and density […]

05.course-distributions【分布图】

In this tutorial you’ll learn all about histograms and density plots. 在本教程中,您将了解直方图和密度图的所有内容。 Set up the notebook 设置笔记本 As always, we begin by setting up the coding environment. (This code is hidden, but you can un-hide it by clicking on the "Code" button immediately below this text, on the right.) 与往常一样,我们首先设置编码环境。 (此代码已隐藏,但您可以通过单击该文本右侧紧邻的“代码”按钮来取消隐藏它。) import pandas as pd […]

04.exercise-scatter-plots【练习:散点图】

This notebook is an exercise in the Data Visualization course. You can reference the tutorial at this link. In this exercise, you will use your new knowledge to propose a solution to a real-world scenario. To succeed, you will need to import data into Python, answer questions using the data, and generate scatter plots to […]

04.course-scatter-plots【散点图】

In this tutorial, you’ll learn how to create advanced scatter plots. 在本教程中,您将学习如何创建高级散点图。 Set up the notebook 设置笔记本 As always, we begin by setting up the coding environment. (This code is hidden, but you can un-hide it by clicking on the "Code" button immediately below this text, on the right.) 与往常一样,我们首先设置编码环境。 (此代码已隐藏,但您可以通过单击该文本右侧紧邻的“代码”按钮来取消隐藏它。) import pandas as pd […]

Scroll to top