机器学习和深度学习入门
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模块1 - Python编程
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 |
模块2 - Python数据分析
| 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 |
模块4 - 机器学习
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)
模块5 - MLOPs
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 |
模块6 - 案例研究
| 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 |
模块7 - 深度学习
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 |