{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 机器学习与社会科学应用"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 作者简介"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"郭峰，复旦大学经济学博士，北京大学金融学博士后，现为上海财经大学公共经济与管理学院投资系教授、博士生导师、系主任，教育部青年长江学者，上海财经大学数实融合与智能治理实验室执行主任，上海财经大学富国ESG研究院副院长，上海财经大学滴水湖高级金融学院双聘教授，北京大学数字金融研究中心特约高级研究员。研究领域包括数字经济与数字金融、机器学习与大数据分析，以及公共经济学等范畴。在《经济研究》（2篇）、《管理世界》（3篇）、《经济学季刊》（6篇）、《管理科学学报》，Research Policy，Journal of Economic Behavior & Organization，China Economic Review 等中英文期刊上发表论文50余篇，其中11篇论文引用率破百，2篇论文引用率破千（《经济学季刊》创刊以来引用率最高5篇论文中的2篇）。另在主流媒体发表经济时评90余篇，出版专著3部，合（参）著多部。主持国家社科基金青年项目、上海市哲学社会科学规划项目、博士后科学基金面上项目等课题10余项。 \n",
"个人主页：http://www.guof1984.net/ "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## “数实融合与智能治理实验室”简介"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"“数实融合与智能治理实验室”是上海财经大学公共经济与管理学院郭峰教授牵头组建的教学科研平台，旨在于利用人工智能、大数据等新工具赋能传统财经学科，以数字经济学与传统财经学科的交叉创新，促进数字经济与实体经济深度融合，助力数字中国高质量发展。实验室历来注重教学与科研的融合，始终秉持着在教学中发掘人才、在科研中培养人才的学术创业初心。实验室相关学术成果发表于《经济研究》《管理世界》《管理科学学报》《经济学季刊》等中文顶级期刊和Research policy，JEBO和CER等英文期刊，实验室开发的Python在线课程已在“智慧树”平台面向全网开放。同时，实验室还通过学术报告、公众号推文等，服务数字经济学术共同体，截止到2024年4月实验室已经举办90多场数字经济、机器学习等相关主题的Workshop，并在公众号上发布80余篇文献或技术推文，公众号关注人数超过10000人。实验室未来将继续聚焦数字经济前沿领域，积极通过科学研究、人才培养、数据库建设、学术交流等活动，致力于建设成为引领学科发展、服务国家战略的重要平台。 "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 实验室公众号"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
""
]
},
"execution_count": 7,
"metadata": {
"image/jpeg": {
"height": 260,
"width": 500
}
},
"output_type": "execute_result"
}
],
"source": [
"#机器学习与数字经济实验室（guofeng0406）\n",
"from IPython.display import Image\n",
"path='D:/python/机器学习与社会科学应用/演示数据/00课前准备工作/'\n",
"Image(filename = path+'公众号二维码.jpg', width=500, height=260)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 课程简介"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"大数据（Big Data）已经成为经济金融活动的重要基础和各学科关注的重点。本课程的目的是讲述机器学习的基本原理及其在经济学大数据分析中的应用，使学生能够了解机器学习的基本理念，掌握有监督学习、无监督学习和自然语言处理代表性算法的基本原理，并能通过Python语言实现这些算法，并通过研读使用机器学习进行实证分析的经济学学术论文，可以将本课程学习到的机器学习原理和算法应用到经济学实证分析当中。 "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 面向对象"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"博士研究生及硕士研究生 "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 先修课程"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"数学分析；概率统计；中级计量经济学；Python语言基础 "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Python网课资源"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"实验室开发的Python课程已在智慧树上面向全网开放 \n",
"课程名称：《Python语言与经济大数据分析》 \n",
"授课老师：郭峰 \n",
"课程平台：智慧树 \n",
"课程网址：https://coursehome.zhihuishu.com/courseHome/1000002241 "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 章节目录"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"第一章 机器学习原理及其启示 \n",
" 第一节 为什么需要学习机器学习 \n",
" 第二节 机器学习的基本任务 \n",
" 第三节 机器学习基本原理 \n",
" 第四节 机器学习的应用与启示 \n",
"第二章 经典回归算法 \n",
" 第一节 OLS回归算法 \n",
" 第二节 岭回归算法 \n",
" 第三节 Lasso回归算法 \n",
" 第四节 算法调参 \n",
"第三章 经典分类算法 \n",
" 第一节 分类算法简介 \n",
" 第二节 K近邻算法 \n",
" 第三节 朴素贝叶斯算法 \n",
" 第四节 决策树算法 \n",
" 第五节 支持向量机算法 \n",
" 第六节 分类算法评估 \n",
"第四章 自然语言处理入门 \n",
" 第一节 自然语言处理的基本任务 \n",
" 第二节 分词 \n",
" 第三节 TF-IDF \n",
" 第四节 文本相似度 \n",
"第五章 集成算法 \n",
" 第一节 集成算法基本原理 \n",
" 第二节 随机森林算法 \n",
" 第三节 梯度提升树算法 \n",
" 第四节 XGBoost算法 \n",
"第六章 无监督学习算法 \n",
" 第一节 无监督学习简介 \n",
" 第二节 聚类算法 \n",
" 第三节 降维算法 \n",
" 第四节 LDA主题模型 \n",
"第七章 深度学习 \n",
" 第一节 神经网络基本原理与前馈神经网络 \n",
" 第二节 卷积神经网络 \n",
" 第三节 循环神经网络 \n",
" 第四节 Word2vec词嵌入算法 \n",
" 第五节 大语言模型简介 \n",
" 第八章 特征工程入门与实践 \n",
" 第一节 特征工程介绍 \n",
" 第二节 特征理解：探索性分析 \n",
" 第三节 特征增强：清洗数据 \n",
" 第四节 特征构造：生成新数据 \n",
" 第五节 特征选择：筛选属性 \n",
" 第六节 特征转换：数据降维 \n",
" 第九章 机器学习与因果识别 \n",
" 第一节 机器学习助力因果识别的基本逻辑 \n",
" 第二节 更好是被和控制混淆因素 \n",
" 第三节 更好地构建对照组 \n",
" 第四节 更好地识别异质性因果效应 \n",
" 第五节 更好地检验因果关系的外部有效性 \n",
" 第六节 大数据和机器学习对因果识别的冲击 \n",
" 第七节 未来展望 \n",
" 第十章 机器学习与异质性因果政策效应分析 \n",
" 第一节 异质性政策效应评估的价值与传统方法 \n",
" 第二节 传统异质性政策效应评方法的问题 \n",
" 第三节 机器学习在异质性政策效应评估中应用 \n",
" 第四节 机器学习的局限以及未来方向 "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 软件安装与课前准备"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"修改jupyter-notebook默认工作路径的方法\n",
"\n",
"1、开始菜单找到Anaconda3文件夹，在Anaconda3文件夹下找到jupyter-notebook，右键-更多-打开文件位置\n",
"\n",
"2、在打开的文件夹中找到Jupyter-notebook快捷方式，右键-属性，打开后可以看到目标位置有一串路径(不同的人根目录可能不同）\n",
"I:\\Anaconda\\python.exe I:\\Anaconda\\cwp.py I:\\Anaconda I:\\Anaconda\\python.exe I:\\Anaconda\\Scripts\\jupyter-notebook-script.py \"F:\\\"\n",
"\n",
"3、以我电脑为例，我将Anaconda安装到了I盘下面的Anaconda目录下\n",
"因此，前五部分按照这样写即可I:\\Anaconda\\python.exe I:\\Anaconda\\cwp.py I:\\Anaconda I:\\Anaconda\\python.exe I:\\Anaconda\\Scripts\\jupyter-notebook-script.py\n",
"如果你安装到了D盘或者E盘，记得修改盘符为D或者E\n",
"\n",
"4、将最后一部分\"F:\\\"修改成你需要默认打开的文件夹\n",
"\n",
"5、最后的格式如下\n",
"I:\\Anaconda\\python.exe I:\\Anaconda\\cwp.py I:\\Anaconda I:\\Anaconda\\python.exe I:\\Anaconda\\Scripts\\jupyter-notebook-script.py \"F:\\\"\n",
"\n",
"6、大功告成，现在你点击开始菜单中的jupyter-notebook可以快速打开进行工作了"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 讲义与演示数据"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"课程的讲义包括PPT和code课件，PPT用来讲解原理，code用来实操"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"code要放入上图“notebook”文件夹。双击上述图片中的“Jupyter Notebook”，找到相应code，就可以操作。"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"“演示数据”文件夹当中提供了大量来自本人实际工作当中使用的数据，以及网络上找到的资历，供课题演示及学生实际操练使用，将其中的材料放入一个如下目录的文件夹当中：“D:\\python\\机器学习与社会科学应用\\演示数据\\”"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"当然，上述文件夹目录并不是强制的，可以逐一修改为自己喜欢和惯用的路径，只不过本课程所有code都是以此路径为数据打开或保存的路径，逐一修改会比较麻烦"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Tips:如果程序和数据位于同一文件夹下，可以采用相对路径形式打开\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"如readme.txt文件和程序运行目录处于同一文件夹下，可以调用read_csv(\"./read_me.txt\")来打开文件"
]
}
],
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"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
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"codemirror_mode": {
"name": "ipython",
"version": 3
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
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