机器学习和深度学习入门

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</div> <details> <summary><h2>模块1 - Python编程</h2></summary>

主题名称	涵盖内容
Python简介	Python的应用和特性、Hello World程序、标识符及定义规则、数据类型（数值、布尔、字符串、列表、元组、集合和字典）、注释、输入和输出、运算符 - 算术、关系、相等、逻辑、位运算、赋值、三元、身份和成员运算符
Python数据结构（字符串、列表、元组、集合、字典）	字符串 - 创建字符串、索引、切片、分割、连接等，列表 - 初始化、索引、切片、排序、追加等，元组 - 初始化、索引、切片、计数、索引等，集合 - 初始化、无序序列、集合运算等，字典 - 初始化、更新、键、值、项等
控制语句（条件和循环）	条件语句 - 缩进介绍、if语句、if...else语句、if..elif...else语句、嵌套if else语句，循环 - while循环、while...else循环、成员运算符、for循环、for...else循环、嵌套循环、Break和Continue语句、Why else?
函数和模块	函数 - Python函数介绍、函数定义和调用、带参数的函数、返回语句、变量作用域、全局变量，模块 - 模块介绍、导入模块、别名、from...import语句、导入所有、一些重要模块 - math、platform、random、webbrowser等
面向对象编程	类和对象 - 创建类、实例化对象、构造函数、类成员 - 变量和方法，变量类型 - 实例、静态和局部变量，方法类型 - 实例、类和静态方法，访问修饰符 - 公共、私有和受保护，面向对象编程的四大支柱 - 继承、多态、抽象和封装，设置器和获取器，继承与关联
异常处理	错误与异常、语法和缩进错误、try...except块、try...except块中的控制流、带多个except的try、finally块、try...except...else、嵌套try...except...finally、用户自定义异常
文件处理	文件处理介绍、打开和关闭文件、文件对象属性、从文本文件读取数据、向文本文件写入数据、with语句、重命名和删除文件
Web API	应用程序编程接口、印度空间站API、API请求、状态码、查询参数、从API请求获取JSON、处理JSON - dump和load、使用Twitter API
数据库	数据库介绍、SQLite3 - Python连接SQLite3、执行CRUD操作、MySQL - Python连接MySQL、执行CRUD操作、MongoDB - Python连接MongoDB、执行CRUD操作、对象关系映射 - SQLAlchemy ORM、CRUD操作和复杂数据库操作
列表推导式、Lambda、Filter、Map、Reduce	列表推导式、匿名函数、Filter、Map、Reduce、函数别名
面试问题解答	交换两个数、计算阶乘、判断素数、斐波那契序列、Armstrong数、回文数等

</details> <details> <summary><h2>模块2 - Python数据分析</h2></summary> | 主题名称 | 涵盖内容 | | :---: | :---: | | [数据分析框架](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%202%20-%20Python%20for%20Data%20Analysis/01.%20Data%20Analytics%20Framework) | 数据收集、业务理解、**探索性数据分析**、数据准备、模型构建、模型评估、部署、理解跨行业标准数据挖掘流程（**CRISP-DM**）和微软的团队数据科学流程（**TDSP**） | | [Numpy](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%202%20-%20Python%20for%20Data%20Analysis/02.%20Numpy) | 使用**Numpy**进行面向数组的数值计算、创建Numpy数组、Numpy数组的基本操作 - 检查维度、形状、数据类型和项目大小、**为什么使用Numpy**、创建Numpy数组的各种方法、Numpy arange()函数、**Numpy随机模块** - rand()、randn()、randint()、uniform()等、Numpy数组的索引和切片、对Numpy数组应用**数学运算** - add()、subtract()、multiply()、divide()、dot()、matmul()、sum()、log()、exp()等、Numpy数组的**统计运算** - min()、max()、mean()、median()、var()、std()、corrcoef()等、**重塑**Numpy数组、其他主题 - Linspace、排序、堆叠、连接、追加、Where和**Numpy广播** | | [Pandas入门](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%202%20-%20Python%20for%20Data%20Analysis/03.%20Pandas%20for%20Beginners) | Pandas数据结构 - 系列、数据框和面板、**创建系列**、数据访问、使用元组和字典**创建数据框**、**数据框属性** - columns、shape、dtypes、axes、values等、**数据框方法** - head()、tail()、info()、describe()、**处理.csv和.xlsx文件** - read_csv()和read_excel()、**数据框转.csv和.xlsx** - to_csv()和to_excel() | | [高级Pandas操作](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%202%20-%20Python%20for%20Data%20Analysis/04.%20Advance%20Pandas%20Operations) | 涵盖内容 | | [案例研究 - Pandas数据操作](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%202%20-%20Python%20for%20Data%20Analysis/05.%20Case%20Study%20-%20Pandas%20Manipulation) | 涵盖内容 | | [缺失值处理](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%202%20-%20Python%20for%20Data%20Analysis/06.%20Missing%20Value%20Treatment) | 涵盖内容 | | [可视化基础 - Matplotlib和Seaborn](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%202%20-%20Python%20for%20Data%20Analysis/07.%20Visuallization%20Basics%20-%20Matplotlib%20and%20Seaborn) | 涵盖内容 | | [案例研究 - Covid_19_时间序列](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%202%20-%20Python%20for%20Data%20Analysis/08.%20Case%20Study%20-%20Covid_19_TimeSeries) | 涵盖内容 | | [Plotly和Express](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%202%20-%20Python%20for%20Data%20Analysis/09.%20Plotly%20and%20Express) | 涵盖内容 | | [异常值 - 即将推出](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%202%20-%20Python%20for%20Data%20Analysis/10.%20Coming%20Soon) | 涵盖内容 | <details> <summary> <h2>模块3 - 数据分析统计学 </h2> </summary>

主题名称	涵盖内容
正态分布	涵盖内容
中心极限定理	涵盖内容
假设检验	涵盖内容
卡方检验	涵盖内容
进行统计检验	涵盖内容

</details> <details> <summary> <h2>模块4 - 机器学习 </h2> </summary> 1. [使用SKLearn进行数据准备和建模](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%204%20-%20Machine%20Learning/01.%20Data%20Preparation%20and%20Modelling%20with%20sklearn) 2. [处理文本数据](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%204%20-%20Machine%20Learning/02.%20Working%20with%20Text%20Data) 3. [处理图像数据](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%204%20-%20Machine%20Learning/03.%20Working%20with%20Image%20Data) 4. [监督学习算法](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%204%20-%20Machine%20Learning/04.%20Supervised%20ML%20Algorithms) - [K近邻](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%204%20-%20Machine%20Learning/04.%20Supervised%20ML%20Algorithms/01.%20K%20-%20NN) - [线性回归](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%204%20-%20Machine%20Learning/04.%20Supervised%20ML%20Algorithms/02.%20Linear%20Regression) - [逻辑回归](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%204%20-%20Machine%20Learning/04.%20Supervised%20ML%20Algorithms/03.%20Logistic%20Regression) - [梯度下降](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%204%20-%20Machine%20Learning/04.%20Supervised%20ML%20Algorithms/04.%20Gradient%20Descent) - [决策树](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%204%20-%20Machine%20Learning/04.%20Supervised%20ML%20Algorithms/05.%20Decision%20Trees) - [支持向量机](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%204%20-%20Machine%20Learning/04.%20Supervised%20ML%20Algorithms/06.%20Support%20Vector%20Machines) - [特征工程模型](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%204%20-%20Machine%20Learning/04.%20Supervised%20ML%20Algorithms/07.%20ML%20Models%20with%20Feature%20Engineering) - [超参数调优](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%204%20-%20Machine%20Learning/04.%20Supervised%20ML%20Algorithms/08.%20Hyperparameter%20Tuning) - [集成学习](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%204%20-%20Machine%20Learning/04.%20Supervised%20ML%20Algorithms/09.%20Ensembles) 5. [无监督学习算法](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%204%20-%20Machine%20Learning/05.%20Unsupervised%20ML%20Algorithms) - [聚类](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%204%20-%20Machine%20Learning/05.%20Unsupervised%20ML%20Algorithms/01.%20Clustering) - [主成分分析](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%204%20-%20Machine%20Learning/05.%20Unsupervised%20ML%20Algorithms/02.%20PCA) <details> <summary> <h2>模块5 - MLOPs </h2> </summary>

主题名称	涵盖内容
模型序列化和反序列化	涵盖内容
应用程序集成	涵盖内容
MLFlow - 实验跟踪和模型管理	涵盖内容
Prefect - 编排机器学习流程	涵盖内容

</details> <details> <summary> <h2>模块6 - 案例研究 </h2> </summary> | 主题名称 | 涵盖内容 | | :---: | :---: | | [汽车价格预测（回归）](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%206%20-%20Case%20Studies/1.%20Car%20Price%20Prediction) | 涵盖内容 | | [航空公司情感分析（自然语言处理 - 分类）](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%206%20-%20Case%20Studies/2.%20Airline%20Sentiment%20Analyser) | 涵盖内容 | | [成人收入预测（分类）](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%206%20-%20Case%20Studies/3.%20Adult%20Income%20Prediction) | 涵盖内容 | | [Web应用开发 + 序列化和反序列化](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%206%20-%20Case%20Studies/4.%20web_app) | 涵盖内容 | | [AWS部署](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%206%20-%20Case%20Studies/5.%20AWS%20Deployment) | 涵盖内容 | | [Streamlit Heroku部署](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%206%20-%20Case%20Studies/6.%20Streamlit%20Heroku%20Deployment) | 涵盖内容 | | [客户分群](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%206%20-%20Case%20Studies/7.%20Customer%20Segmentation) | 涵盖内容 | | [网络爬虫](https://github.com/bansalkanav/Machine_Learning_and_Deep_Learning/tree/master/Module%206%20-%20Case%20Studies/8.%20Regex%20and%20Webscrapping) | 涵盖内容 | <details> <summary> <h2>模块7 - 深度学习</h2> </summary>

主题名称	涵盖内容
深度学习简介	涵盖内容
训练深度神经网络 + TensorFlow.Keras	涵盖内容
卷积神经网络 + TensorFlow.Keras	涵盖内容
用于图像压缩的自动编码器	涵盖内容
循环神经网络（即将推出）	涵盖内容

</details>