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Title: GitHub - application-user2/ML-notes: notes about machine learning

Open Graph Title: GitHub - application-user2/ML-notes: notes about machine learning

X Title: GitHub - application-user2/ML-notes: notes about machine learning

Description: notes about machine learning. Contribute to application-user2/ML-notes development by creating an account on GitHub.

Open Graph Description: notes about machine learning. Contribute to application-user2/ML-notes development by creating an account on GitHub.

X Description: notes about machine learning. Contribute to application-user2/ML-notes development by creating an account on GitHub.

Opengraph URL: https://github.com/application-user2/ML-notes

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https://patch-diff.githubusercontent.com/application-user2/ML-notes#html链接
1_Introductionhttps://sakura-gh.github.io/ML-notes/ML-notes-html/1_Introduction.html
2_Regression Case Studyhttps://sakura-gh.github.io/ML-notes/ML-notes-html/2_Regression-Case-Study.html
3_Regression demo(Adagrad)https://sakura-gh.github.io/ML-notes/ML-notes-html/3_Regression-demo(Adagrad).html
4_Where does the error come fromhttps://sakura-gh.github.io/ML-notes/ML-notes-html/4_Where-does-the-error-come-from.html
5_Gradient Descenthttps://sakura-gh.github.io/ML-notes/ML-notes-html/5_Gradient-Descent.html
6_Classificationhttps://sakura-gh.github.io/ML-notes/ML-notes-html/6_Classification.html
7_Logistic Regressionhttps://sakura-gh.github.io/ML-notes/ML-notes-html/7_Logistic-Regression.html
8_Deep Learninghttps://sakura-gh.github.io/ML-notes/ML-notes-html/8_Deep-Learning.html
9_Backpropagationhttps://sakura-gh.github.io/ML-notes/ML-notes-html/9_Backpropagation.html
10_Kerashttps://sakura-gh.github.io/ML-notes/ML-notes-html/10_Keras.html
11_Convolutional Neural Network part1https://sakura-gh.github.io/ML-notes/ML-notes-html/11_Convolutional-Neural-Network-part1.html
12_Convolutional Neural Network part2https://sakura-gh.github.io/ML-notes/ML-notes-html/12_Convolutional-Neural-Network-part2.html
13_Tips for Deep Learninghttps://sakura-gh.github.io/ML-notes/ML-notes-html/13_Tips-for-Deep-Learning.html
14_Why Deephttps://sakura-gh.github.io/ML-notes/ML-notes-html/14_Why-Deep.html
15_Semi-supervised Learninghttps://sakura-gh.github.io/ML-notes/ML-notes-html/15_Semi-supervised-Learning.html
16_Unsupervised Learning Introductionhttps://sakura-gh.github.io/ML-notes/ML-notes-html/16_Unsupervised-Learning-Introduction.html
17_Unsupervised Learning PCA part1https://sakura-gh.github.io/ML-notes/ML-notes-html/17_Unsupervised-Learning-PCA-part1.html
18_Unsupervised Learning PCA part2https://sakura-gh.github.io/ML-notes/ML-notes-html/18_Unsupervised-Learning-PCA-part2.html
19_Matrix Factorizationhttps://sakura-gh.github.io/ML-notes/ML-notes-html/19_Matrix-Factorization.html
20_Unsupervised Learning Word Embeddinghttps://sakura-gh.github.io/ML-notes/ML-notes-html/20_Unsupervised-Learning-Word-Embedding.html
21_Unsupervised Learning Neighbor Embeddinghttps://sakura-gh.github.io/ML-notes/ML-notes-html/21_Unsupervised-Learning-Neighbor-Embedding.html
22_Unsupervised Learning Deep Auto-encoderhttps://sakura-gh.github.io/ML-notes/ML-notes-html/22_Unsupervised-Learning-Deep-Auto-encoder.html
23_Unsupervised Learning Generationhttps://sakura-gh.github.io/ML-notes/ML-notes-html/23_Unsupervised-Generation.html
24_Transfer Learninghttps://sakura-gh.github.io/ML-notes/ML-notes-html/24_Transfer-Learning.html
25_Support Vector Machinehttps://sakura-gh.github.io/ML-notes/ML-notes-html/25_Support-Vector-Machine.html
26_Recurrent Neural Network part1https://sakura-gh.github.io/ML-notes/ML-notes-html/26_Recurrent-Neural-Network-part1.html
27_Recurrent Neural Network part2https://sakura-gh.github.io/ML-notes/ML-notes-html/27_Recurrent-Neural-Network-part2.html
https://patch-diff.githubusercontent.com/application-user2/ML-notes#csdn博客链接
机器学习系列1-机器学习概念及介绍https://blog.csdn.net/weixin_44406200/article/details/104060561
机器学习系列2-回归案例研究https://blog.csdn.net/weixin_44406200/article/details/104071036
梯度下降代码举例：Gradient Descent Demo(Adagrad)https://blog.csdn.net/weixin_44406200/article/details/104075986
机器学习系列4-模型的误差来源及减少误差的方法https://blog.csdn.net/weixin_44406200/article/details/104088554
机器学习系列5-梯度下降法https://blog.csdn.net/weixin_44406200/article/details/104256006
机器学习系列6-分类问题(概率生成模型)https://blog.csdn.net/weixin_44406200/article/details/104272160
机器学习系列7-逻辑回归https://blog.csdn.net/weixin_44406200/article/details/104288916
机器学习系列8-深度学习简介https://blog.csdn.net/weixin_44406200/article/details/104299958
机器学习系列9-反向传播https://blog.csdn.net/weixin_44406200/article/details/104310991
机器学习系列10-手写数字识别(Keras2.0)https://blog.csdn.net/weixin_44406200/article/details/104328947
机器学习系列11-卷积神经网络CNN part1https://blog.csdn.net/weixin_44406200/article/details/104370738
机器学习系列12-卷积神经网络CNN part2https://blog.csdn.net/weixin_44406200/article/details/104392592
机器学习系列13-深度学习的技巧和优化方法https://blog.csdn.net/weixin_44406200/article/details/104430737
机器学习系列14-为什么要做“深度”学习https://blog.csdn.net/weixin_44406200/article/details/104452873
机器学习系列15-半监督学习https://blog.csdn.net/weixin_44406200/article/details/106991717
机器学习系列16-无监督学习引言https://blog.csdn.net/weixin_44406200/article/details/107029531
机器学习系列17-无监督学习之PCA推导(Ⅰ)https://blog.csdn.net/weixin_44406200/article/details/107082637
机器学习系列18-无监督学习之PCA深入探讨(Ⅱ)https://blog.csdn.net/weixin_44406200/article/details/107082680
机器学习系列19-矩阵分解&推荐系统初步https://blog.csdn.net/weixin_44406200/article/details/107099894
机器学习系列20-无监督学习之词嵌入https://blog.csdn.net/weixin_44406200/article/details/107168089
机器学习系列21-无监督学习之近邻嵌入https://blog.csdn.net/weixin_44406200/article/details/107305230
机器学习系列22-无监督学习之自编码器https://blog.csdn.net/weixin_44406200/article/details/107305267
机器学习系列23-无监督学习之生成模型https://blog.csdn.net/weixin_44406200/article/details/107305305
机器学习系列24-迁移学习https://blog.csdn.net/weixin_44406200/article/details/107305326
机器学习系列25-支持向量机https://blog.csdn.net/weixin_44406200/article/details/107693177
机器学习系列26-循环神经网络RNN(Ⅰ)https://blog.csdn.net/weixin_44406200/article/details/107693331
机器学习系列27-循环神经网络RNN(Ⅱ)https://blog.csdn.net/weixin_44406200/article/details/107812374
https://patch-diff.githubusercontent.com/application-user2/ML-notes#代码链接
Gradient Descent Demo(Adagrad)https://sakura-gh.github.io/ML-notes/code/Gradient-Descent-Demo/Gradient-Descent-Demo.html
手写数字识别(Keras2.0)https://github.com/Sakura-gh/ML-notes/blob/master/code/Digits-Detection/digits-detection.py
手写数字识别CNN实现(Keras2.0)https://github.com/Sakura-gh/ML-notes/blob/master/code/Digits-Detection/digits-detection-cnn.py
Keras实战小经验https://github.com/Sakura-gh/ML-notes/blob/master/keras-tips.md
PyTorch简易入门https://github.com/Sakura-gh/ML-notes/blob/master/code/pytorch
https://patch-diff.githubusercontent.com/application-user2/ML-notes#license
https://patch-diff.githubusercontent.com/application-user2/ML-notes#温馨提示
https://patch-diff.githubusercontent.com/application-user2/ML-notes#赞赏作者
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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

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URLs of crawlers that visited me.