Skip to content

R2covery/2022-Machine-Learning-Specialization

 
 

Repository files navigation

2022-Machine-Learning-Specialization

吴恩达2022新版机器学习 machine learning specialization
课程官网:https://www.coursera.org/specializations/machine-learning-introduction
bilibili:https://www.bilibili.com/video/BV19B4y1W76i
github:https://github.com/kaieye/2022-Machine-Learning-Specialization
课程代码及测验内容已更新完毕
欢迎pull request,无论是补充学习文件还是优化md笔记
交流群:772590431

课程大纲

Machine learning specialization课程共分为三部分

  • 第一部分:Supervised Machine Learning: Regression and Classification
  • 第二部分:Advanced Learning Algorithms
  • 第三部分:Unsupervised Learning: Recommenders, Reinforcement Learning

目前上传的是第二部分,course1的sildes(ppt)已更新完毕

Machine Learning Specialization by Andrew Ng in 2022
Course website:https://www.coursera.org/specializations/machine-learning-introduction
bilibili:https://www.bilibili.com/video/BV19B4y1W76i
github:https://github.com/kaieye/2022-Machine-Learning-Specialization
Course code and test content have been updated
Welcome to pull requests, whether it is to supplement learning files or markdown notes

Course Outline

Machine learning specialization is divided into 3 parts

  • Part 1:Supervised Machine Learning: Regression and Classification
  • Part 2:Advanced Learning Algorithms
  • Part 3:Unsupervised Learning: Recommenders, Reinforcement Learning

The second part is currently Uploaded
the slides of course 1 have been updated

环境配置

按照操作系统类型安装python(官方使用的环境为3.7.6),安装方式各异。安装成功后在cmd/bash中定位到该文件夹,并使用如下命令安装依赖。

pip install -r requirements.txt

mac/linux用户需将pip切换成pip3

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 92.6%
  • Python 7.4%