René's URL Explorer Experiment


Title: GitHub - bartgw/100-Days-of-ML-Code-Chinese-Version: Chinese Translation for Machine Learning Infographics · GitHub

Open Graph Title: GitHub - bartgw/100-Days-of-ML-Code-Chinese-Version: Chinese Translation for Machine Learning Infographics

X Title: GitHub - bartgw/100-Days-of-ML-Code-Chinese-Version: Chinese Translation for Machine Learning Infographics

Description: Chinese Translation for Machine Learning Infographics - bartgw/100-Days-of-ML-Code-Chinese-Version

Open Graph Description: Chinese Translation for Machine Learning Infographics - bartgw/100-Days-of-ML-Code-Chinese-Version

X Description: Chinese Translation for Machine Learning Infographics - bartgw/100-Days-of-ML-Code-Chinese-Version

Opengraph URL: https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version

X: @github

direct link

Domain: github.com

route-pattern/:user_id/:repository
route-controllerfiles
route-actiondisambiguate
fetch-noncev2:106821f2-e16d-993e-c06a-e2f8947a33cd
current-catalog-service-hashf3abb0cc802f3d7b95fc8762b94bdcb13bf39634c40c357301c4aa1d67a256fb
request-idB7C6:25FD2A:32E6CF8:4428E4D:6A65529F
html-safe-nonce89b5be864ff58ae94b6296c1c16f281aca2fc4b83c9fd4d13913b3acb837956e
visitor-payloadeyJyZWZlcnJlciI6IiIsInJlcXVlc3RfaWQiOiJCN0M2OjI1RkQyQTozMkU2Q0Y4OjQ0MjhFNEQ6NkE2NTUyOUYiLCJ2aXNpdG9yX2lkIjoiODU2NzgzMTY5OTk0MjM2MzgwNyIsInJlZ2lvbl9lZGdlIjoiaWFkIiwicmVnaW9uX3JlbmRlciI6ImlhZCJ9
visitor-hmac8ba9f420522c4ef7f39ed9cdc3c3854ca8b4a27d160498560ae4d36c644f06b9
hovercard-subject-tagrepository:522536310
github-keyboard-shortcutsrepository,copilot
google-site-verificationApib7-x98H0j5cPqHWwSMm6dNU4GmODRoqxLiDzdx9I
octolytics-urlhttps://collector.github.com/github/collect
analytics-location//
fb:app_id1401488693436528
apple-itunes-appapp-id=1477376905, app-argument=https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version
twitter:imagehttps://opengraph.githubassets.com/c7ab8ca9143b5c83ea0b84c63a631aa0184169e0b0b30b6ad130e1f2284ec10d/bartgw/100-Days-of-ML-Code-Chinese-Version
twitter:cardsummary_large_image
og:imagehttps://opengraph.githubassets.com/c7ab8ca9143b5c83ea0b84c63a631aa0184169e0b0b30b6ad130e1f2284ec10d/bartgw/100-Days-of-ML-Code-Chinese-Version
og:image:altChinese Translation for Machine Learning Infographics - bartgw/100-Days-of-ML-Code-Chinese-Version
og:image:width1200
og:image:height600
og:site_nameGitHub
og:typeobject
hostnamegithub.com
expected-hostnamegithub.com
None52c76df668885aaff23b50bdca1fa1ea44ac9c1553e888ebc70ff1e4daa4625b
turbo-cache-controlno-cache
go-importgithub.com/bartgw/100-Days-of-ML-Code-Chinese-Version git https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version.git
octolytics-dimension-user_id90127590
octolytics-dimension-user_loginbartgw
octolytics-dimension-repository_id522536310
octolytics-dimension-repository_nwobartgw/100-Days-of-ML-Code-Chinese-Version
octolytics-dimension-repository_publictrue
octolytics-dimension-repository_is_forktrue
octolytics-dimension-repository_parent_id143617378
octolytics-dimension-repository_parent_nwoAvik-Jain/100-Days-of-ML-Code-Chinese-Version
octolytics-dimension-repository_network_root_id143617378
octolytics-dimension-repository_network_root_nwoAvik-Jain/100-Days-of-ML-Code-Chinese-Version
turbo-body-classeslogged-out env-production page-responsive
disable-turbofalse
browser-stats-urlhttps://api.github.com/_private/browser/stats
browser-errors-urlhttps://api.github.com/_private/browser/errors
release309153364422b3c499922d1a2a6404910a58ed8e
ui-targetfull
theme-color#1e2327
color-schemelight dark

Links:

Skip to contenthttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#start-of-content
https://github.com/
Sign in https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fbartgw%2F100-Days-of-ML-Code-Chinese-Version
GitHub CopilotWrite better code with AIhttps://github.com/features/copilot
GitHub Copilot appDirect agents from issue to mergehttps://github.com/features/ai/github-app
MCP RegistryNewIntegrate external toolshttps://github.com/mcp
ActionsAutomate any workflowhttps://github.com/features/actions
CodespacesInstant dev environmentshttps://github.com/features/codespaces
IssuesPlan and track workhttps://github.com/features/issues
Code ReviewManage code changeshttps://github.com/features/code-review
Code QualityEnforce quality at mergehttps://github.com/features/code-quality
GitHub Advanced SecurityFind and fix vulnerabilitieshttps://github.com/security/advanced-security
Code securitySecure your code as you buildhttps://github.com/security/advanced-security/code-security
Secret protectionStop leaks before they starthttps://github.com/security/advanced-security/secret-protection
Why GitHubhttps://github.com/why-github
Documentationhttps://docs.github.com
Bloghttps://github.blog
Changeloghttps://github.blog/changelog
Marketplacehttps://github.com/marketplace
View all featureshttps://github.com/features
Enterpriseshttps://github.com/enterprise
Small and medium teamshttps://github.com/team
Startupshttps://github.com/enterprise/startups
Nonprofitshttps://github.com/solutions/industry/nonprofits
App Modernizationhttps://github.com/solutions/use-case/app-modernization
DevSecOpshttps://github.com/solutions/use-case/devsecops
DevOpshttps://github.com/solutions/use-case/devops
CI/CDhttps://github.com/solutions/use-case/ci-cd
View all use caseshttps://github.com/solutions/use-case
Healthcarehttps://github.com/solutions/industry/healthcare
Financial serviceshttps://github.com/solutions/industry/financial-services
Manufacturinghttps://github.com/solutions/industry/manufacturing
Governmenthttps://github.com/solutions/industry/government
View all industrieshttps://github.com/solutions/industry
View all solutionshttps://github.com/solutions
AIhttps://github.com/resources/articles?topic=ai
Software Developmenthttps://github.com/resources/articles?topic=software-development
DevOpshttps://github.com/resources/articles?topic=devops
Securityhttps://github.com/resources/articles?topic=security
View all topicshttps://github.com/resources/articles
Customer storieshttps://github.com/customer-stories
Events & webinarshttps://github.com/resources/events
Ebooks & reportshttps://github.com/resources/whitepapers
Business insightshttps://github.com/solutions/executive-insights
GitHub Skillshttps://skills.github.com
Documentationhttps://docs.github.com
Customer supporthttps://support.github.com
Community forumhttps://github.com/orgs/community/discussions
Trust centerhttps://github.com/trust-center
Partnershttps://github.com/partners
View all resourceshttps://github.com/resources
GitHub SponsorsFund open source developershttps://github.com/open-source/sponsors
Security Labhttps://securitylab.github.com
Maintainer Communityhttps://maintainers.github.com
Acceleratorhttps://github.com/open-source/accelerator
GitHub Starshttps://stars.github.com
Archive Programhttps://archiveprogram.github.com
Topicshttps://github.com/topics
Trendinghttps://github.com/trending
Collectionshttps://github.com/collections
Enterprise platformAI-powered developer platformhttps://github.com/enterprise
GitHub Advanced SecurityEnterprise-grade security featureshttps://github.com/security/advanced-security
Copilot for BusinessEnterprise-grade AI featureshttps://github.com/features/copilot/copilot-business
Premium SupportEnterprise-grade 24/7 supporthttps://github.com/enterprise/premium-support
Pricinghttps://github.com/pricing
Search syntax tipshttps://docs.github.com/search-github/github-code-search/understanding-github-code-search-syntax
documentationhttps://docs.github.com/search-github/github-code-search/understanding-github-code-search-syntax
Sign in https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fbartgw%2F100-Days-of-ML-Code-Chinese-Version
Sign up https://github.com/signup?ref_cta=Sign+up&ref_loc=header+logged+out&ref_page=%2F%3Cuser-name%3E%2F%3Crepo-name%3E&source=header-repo&source_repo=bartgw%2F100-Days-of-ML-Code-Chinese-Version
Reloadhttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version
Reloadhttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version
Reloadhttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version
bartgw https://github.com/bartgw
100-Days-of-ML-Code-Chinese-Versionhttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version
Avik-Jain/100-Days-of-ML-Code-Chinese-Versionhttps://github.com/Avik-Jain/100-Days-of-ML-Code-Chinese-Version
Notifications https://github.com/login?return_to=%2Fbartgw%2F100-Days-of-ML-Code-Chinese-Version
Fork 0 https://github.com/login?return_to=%2Fbartgw%2F100-Days-of-ML-Code-Chinese-Version
Star 0 https://github.com/login?return_to=%2Fbartgw%2F100-Days-of-ML-Code-Chinese-Version
Code https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version
Pull requests 0 https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/pulls
Actions https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/actions
Projects https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/projects
Security and quality 0 https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/security
Insights https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/pulse
Code https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version
Pull requests https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/pulls
Actions https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/actions
Projects https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/projects
Security and quality https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/security
Insights https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/pulse
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version
Brancheshttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/branches
Tagshttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/tags
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/branches
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/tags
23 Commitshttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/commits/master/
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/commits/master/
Codehttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/tree/master/Code
Codehttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/tree/master/Code
Info-graphshttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/tree/master/Info-graphs
Info-graphshttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/tree/master/Info-graphs
Other Docshttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/tree/master/Other%20Docs
Other Docshttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/tree/master/Other%20Docs
.gitignorehttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/blob/master/.gitignore
.gitignorehttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/blob/master/.gitignore
LICENSEhttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/blob/master/LICENSE
LICENSEhttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/blob/master/LICENSE
README.mdhttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/blob/master/README.md
README.mdhttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/blob/master/README.md
README.md.bakhttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/blob/master/README.md.bak
README.md.bakhttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/blob/master/README.md.bak
READMEhttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version
Licensehttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#机器学习100天
Avik-Jainhttps://github.com/Avik-Jain/100-Days-Of-ML-Code
中文最新版https://github.com/MachineLearning100/100-Days-Of-ML-Code
FAQhttps://github.com/MLEveryday/100-Days-Of-ML-Code/blob/master/FAQ.MD
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#目录
数据预处理https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86--%E7%AC%AC1%E5%A4%A9
简单线性回归https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#%E7%AE%80%E5%8D%95%E7%BA%BF%E6%80%A7%E5%9B%9E%E5%BD%92--%E7%AC%AC2%E5%A4%A9
多元线性回归https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#%E5%A4%9A%E5%85%83%E7%BA%BF%E6%80%A7%E5%9B%9E%E5%BD%92--%E7%AC%AC3%E5%A4%A9
逻辑回归https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92--%E7%AC%AC4%E5%A4%A9
k近邻法(k-NN)https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#k%E8%BF%91%E9%82%BB%E6%B3%95k-nn--%E7%AC%AC7%E5%A4%A9
支持向量机(SVM)https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BAsvm--%E7%AC%AC12%E5%A4%A9
决策树https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#%E5%86%B3%E7%AD%96%E6%A0%91--%E7%AC%AC23%E5%A4%A9
随机森林https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97--%E7%AC%AC33%E5%A4%A9
K-均值聚类https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#k-%E5%9D%87%E5%80%BC%E8%81%9A%E7%B1%BB--%E7%AC%AC43%E5%A4%A9
层次聚类https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#%E5%B1%82%E6%AC%A1%E8%81%9A%E7%B1%BB--%E7%AC%AC54%E5%A4%A9
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#数据预处理--第1天
数据预处理实现https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Code/Day%201_Data_Preprocessing.md
https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%201.jpg
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#简单线性回归--第2天
简单线性回归实现https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Code/Day%202_Simple_Linear_Regression.md
https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%202.jpg
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#多元线性回归--第3天
多元线性回归实现https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Code/Day%203_Multiple_Linear_Regression.md
https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%203.png
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#逻辑回归--第4天
https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%204.jpg
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#逻辑回归--第5天
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#逻辑回归--第6天
逻辑回归实现https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Code/Day%206_Logistic_Regression.md
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#k近邻法k-nn--第7天
https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%207.jpg
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#逻辑回归背后的数学--第8天
这篇文章https://towardsdatascience.com/logistic-regression-detailed-overview-46c4da4303bc
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#支持向量机svm--第9天
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#支持向量机和k近邻法--第10天
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#k近邻法k-nn--第11天
K近邻法(k-NN)实现https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Code/Day%2011_K-NN.md
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#支持向量机svm--第12天
https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%2012.jpg
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#支持向量机svm--第13天
SVM实现https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Code/Day%2013_SVM.md
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#支持向量机svm的实现--第14天
此处https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Code/Day%2013_SVM.py
此处https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Code/Day%2013_SVM.ipynb
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#朴素贝叶斯分类器naive-bayes-classifier和黑盒机器学习black-box-machine-learning--第15天
Bloomberghttps://bloomberg.github.io/foml/#home
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#通过内核技巧实现支持向量机--第16天
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#在coursera开始深度学习的专业课程--第17天
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#继续coursera上的深度学习专业课程--第18天
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#学习问题和yaser-abu-mostafa教授--第19天
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#深度学习专业课程2--第20天
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#网页搜罗--第21天
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#学习还可行吗--第22天
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#决策树--第23天
https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%2023%20-%20Chinese.jpg
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#统计学习理论的介绍--第24天
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#决策树--第25天
决策树实现https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Code/Day%2025_Decision_Tree.md
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#跳到复习线性代数--第26天
3Blue1Brownhttps://www.youtube.com/channel/UCYO_jab_esuFRV4b17AJtAw
这里https://space.bilibili.com/88461692/#/channel/detail?cid=9450
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#跳到复习线性代数--第27天
这里https://space.bilibili.com/88461692/#/channel/detail?cid=9450
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#跳到复习线性代数--第28天
这里https://space.bilibili.com/88461692/#/channel/detail?cid=9450
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#跳到复习线性代数--第29天
这里https://space.bilibili.com/88461692/#/channel/detail?cid=9450
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#微积分的本质--第30天
这里https://space.bilibili.com/88461692/#/channel/detail?cid=13407
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#微积分的本质--第31天
这里https://space.bilibili.com/88461692/#/channel/detail?cid=13407
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#微积分的本质--第32天
这里https://space.bilibili.com/88461692/#/channel/detail?cid=13407
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#随机森林--第33天
https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%2033.png
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#随机森林--第34天
随机森林实现https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Code/Day%2034_Random_Forests.md
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#什么是神经网络--深度学习第1章--第-35天
这里https://space.bilibili.com/88461692/#/channel/detail?cid=26587
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#梯度下降法神经网络如何学习--深度学习第2章--第36天
这里https://space.bilibili.com/88461692/#/channel/detail?cid=26587
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#反向传播法究竟做什么--深度学习第3章--第37天
这里https://space.bilibili.com/88461692/#/channel/detail?cid=26587
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#反向传播法演算--深度学习第4章--第38天
这里https://space.bilibili.com/88461692/#/channel/detail?cid=26587
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#第1部分--深度学习基础pythontensorflow和keras--第39天
这里https://www.youtube.com/watch?v=wQ8BIBpya2k&t=19s&index=2&list=PLQVvvaa0QuDfhTox0AjmQ6tvTgMBZBEXN
notebookhttps://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Code/Day%2039.ipynb
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#第2部分--深度学习基础pythontensorflow和keras--第40天
这里https://www.youtube.com/watch?v=wQ8BIBpya2k&t=19s&index=2&list=PLQVvvaa0QuDfhTox0AjmQ6tvTgMBZBEXN
notebookhttps://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Code/Day%2040.ipynb
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#第3部分--深度学习基础pythontensorflow和keras--第41天
这里https://www.youtube.com/watch?v=wQ8BIBpya2k&t=19s&index=2&list=PLQVvvaa0QuDfhTox0AjmQ6tvTgMBZBEXN
notebookhttps://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Code/Day%2041.ipynb
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#第4部分--深度学习基础pythontensorflow和keras--第42天
这里https://www.youtube.com/watch?v=wQ8BIBpya2k&t=19s&index=2&list=PLQVvvaa0QuDfhTox0AjmQ6tvTgMBZBEXN
notebookhttps://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Code/Day%2042.ipynb
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#k-均值聚类--第43天
作者网站http://www.avikjain.me/
动画http://shabal.in/visuals/kmeans/6.html
https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%2043.jpg
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#k-均值聚类--第44天
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#深入研究--numpy--第45天
这里https://github.com/jakevdp/PythonDataScienceHandbook
高清中文版pdfhttps://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Other%20Docs/Python%E6%95%B0%E6%8D%AE%E7%A7%91%E5%AD%A6%E6%89%8B%E5%86%8C.zip
2 NumPy入门https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.00-Introduction-to-NumPy.ipynb
2.1 理解Python中的数据类型https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.01-Understanding-Data-Types.ipynb
2.2 NumPy数组基础https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.02-The-Basics-Of-NumPy-Arrays.ipynb
2.3 NumPy数组的计算：通用函数https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.03-Computation-on-arrays-ufuncs.ipynb
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#深入研究--numpy--第46天
2.4 聚合：最小值、最大值和其他值https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.04-Computation-on-arrays-aggregates.ipynb
2.5 数组的计算：广播https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.05-Computation-on-arrays-broadcasting.ipynb
2.6 比较、掩码和布尔运算https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.06-Boolean-Arrays-and-Masks.ipynb
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#深入研究--numpy--第47天
2.7 花哨的索引https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.07-Fancy-Indexing.ipynb
2.8 数组的排序https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.08-Sorting.ipynb
2.9 结构化数据：NumPy的结构化数组https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.09-%3Cbr%3EStructured-Data-NumPy.ipynb
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#深入研究--pandas--第48天
3 Pandas数据处理https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.00-Introduction-to-Pandas.ipynb
3.1 Pandas对象简介https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.01-Introducing-Pandas-Objects.ipynb
3.2 数据取值与选择https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.02-Data-Indexing-and-Selection.ipynb
3.3 Pandas数值运算方法https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.03-Operations-in-Pandas.ipynb
3.4 处理缺失值https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.04-Missing-Values.ipynb
3.5 层级索引https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.05-Hierarchical-Indexing.ipynb
3.6 合并数据集：ConCat和Append方法https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.06-Concat-And-Append.ipynb
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#深入研究--pandas--第49天
3.7 合并数据集：合并与连接https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.07-Merge-and-Join.ipynb
3.8 累计与分组https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.08-Aggregation-and-Grouping.ipynb
3.9 数据透视表https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.09-Pivot-Tables.ipynb
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#深入研究--pandas--第50天
3.10 向量化字符串操作https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.10-Working-With-Strings.ipynb
3.11 处理时间序列https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.11-Working-with-Time-Series.ipynb
3.12 高性能Pandas：eval()与query()https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.12-Performance-Eval-and-Query.ipynb
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#深入研究--matplotlib--第51天
4 Matplotlib数据可视化https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.00-Introduction-To-Matplotlib.ipynb
4.1 简易线形图https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.01-Simple-Line-Plots.ipynb
4.2 简易散点图https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.02-Simple-Scatter-Plots.ipynb
4.3 可视化异常处理https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.03-Errorbars.ipynb
4.4 密度图与等高线图https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.04-Density-and-Contour-Plots.ipynb
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#深入研究--matplotlib--第52天
4.5 直方图https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.05-Histograms-and-Binnings.ipynb
4.6 配置图例https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.06-Customizing-Legends.ipynb
4.7 配置颜色条https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.07-Customizing-Colorbars.ipynb
4.8 多子图https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.08-Multiple-Subplots.ipynb
4.9 文字与注释https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.09-Text-and-Annotation.ipynb
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#深入研究--matplotlib--第53天
4.12 画三维图https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.12-Three-Dimensional-Plotting.ipynb
https://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#层次聚类--第54天
动画演示https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Other%20Docs/%E5%B1%82%E6%AC%A1%E8%81%9A%E7%B1%BB.gif
https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%2054.jpg
Readmehttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#readme-ov-file
Licensehttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version#License-1-ov-file
Activityhttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/activity
0 starshttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/stargazers
0 watchinghttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/watchers
0 forkshttps://github.com/bartgw/100-Days-of-ML-Code-Chinese-Version/forks
Report repositoryhttps://github.com/contact/report-content?content_url=https%3A%2F%2Fgithub.com%2Fbartgw%2F100-Days-of-ML-Code-Chinese-Version&report=bartgw+%28user%29
https://github.com
Termshttps://docs.github.com/site-policy/github-terms/github-terms-of-service
Privacyhttps://docs.github.com/site-policy/privacy-policies/github-privacy-statement
Securityhttps://github.com/security
Statushttps://www.githubstatus.com/
Communityhttps://github.community/
Docshttps://docs.github.com/
Contacthttps://support.github.com?tags=dotcom-footer

Viewport: width=device-width

URLs of crawlers that visited me.