<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[weixin_45804601的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/weixin_45804601</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; weixin_45804601]]></copyright><item><title><![CDATA[Python 多进程， 多线程(bushi)，协程(异步)]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/139787506</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/139787506</guid><author>weixin_45804601</author><pubDate>Wed, 19 Jun 2024 02:36:24 +0800</pubDate><description><![CDATA[多进程，多线程，异步，协程]]></description><category></category></item><item><title><![CDATA[DEVITO-GPU安装指南]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/135464810</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/135464810</guid><author>weixin_45804601</author><pubDate>Mon, 08 Jan 2024 19:40:43 +0800</pubDate><description><![CDATA[然后找到examples/seismic/abc_methods/01_introduction.ipynb那个文件，所有代码运行一遍，之前如果python setup.py install有些包比如sympy等可能没安装成功，你运行代码的时候就会告诉你缺啥包，这时候用刚才方式登录root，用pip再安装缺失的包（注意观察安装完之后pip的信息，可能会缺很多，pip会给提示，按照提示继续装）直到装的01_introduction.ipynb完全跑通，环境就配好了，可以在任何地方新建自己的项目跑。]]></description><category></category></item><item><title><![CDATA[《统计学习方法》Chapter.14聚类方法]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/128894779</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/128894779</guid><author>weixin_45804601</author><pubDate>Sun, 05 Feb 2023 23:04:24 +0800</pubDate><description><![CDATA[《统计学习方法》Chapter.14聚类方法笔记理论+代码]]></description><category></category></item><item><title><![CDATA[《统计学习方法》Chapter.8 提升方法----AdaBoost]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/128176503</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/128176503</guid><author>weixin_45804601</author><pubDate>Sun, 04 Dec 2022 20:05:12 +0800</pubDate><description><![CDATA[《统计学习方法》第二版学习笔记 Chapter.8 提升方法 理论+Sklearn实现]]></description><category></category></item><item><title><![CDATA[支持向量机SVM（包括线性核、多项式核、高斯核）python手写实现+代码框架说明]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/127985720</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/127985720</guid><author>weixin_45804601</author><pubDate>Tue, 22 Nov 2022 16:49:04 +0800</pubDate><description><![CDATA[支持向量机SVM（包括线性核、多项式核、高斯核）python手写实现+代码框架说明]]></description><category></category></item><item><title><![CDATA[《统计学习方法》Chapter.7 支持向量机（SVM）]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/127952840</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/127952840</guid><author>weixin_45804601</author><pubDate>Sun, 20 Nov 2022 19:42:49 +0800</pubDate><description><![CDATA[《统计学习方法》第二版学习笔记 Chapter.7 支持向量机 理论+手写代码实现+Sklearn实现]]></description><category></category></item><item><title><![CDATA[《统计学习方法》Chapter.6.1 逻辑斯谛回归（Logistic Regression）]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/127838323</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/127838323</guid><author>weixin_45804601</author><pubDate>Sun, 13 Nov 2022 22:09:09 +0800</pubDate><description><![CDATA[《统计学习方法》第二版学习笔记 Chapter.6.1 逻辑斯谛回归模型 理论+sklearn实现]]></description><category></category></item><item><title><![CDATA[决策树底层思想，决策树的损失函数与极大似然函数理解]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/127611787</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/127611787</guid><author>weixin_45804601</author><pubDate>Mon, 31 Oct 2022 11:09:51 +0800</pubDate><description><![CDATA[决策树底层思想，决策树的损失函数与极大似然函数理解]]></description><category></category></item><item><title><![CDATA[《统计学习方法》Chapter.5 决策树]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/127607090</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/127607090</guid><author>weixin_45804601</author><pubDate>Sun, 30 Oct 2022 23:12:57 +0800</pubDate><description><![CDATA[《统计学习方法》第二版学习笔记 Chapter.5 决策树 理论+sklearn实现]]></description><category></category></item><item><title><![CDATA[《统计学习方法》Chapter.4 朴素贝叶斯（naive Bayes）]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/127456402</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/127456402</guid><author>weixin_45804601</author><pubDate>Sat, 22 Oct 2022 00:50:57 +0800</pubDate><description><![CDATA[《统计学习方法》第二版学习笔记 Chapter.4 朴素贝叶斯（naive Bayes）理论+手写实现+sklearn实现]]></description><category></category></item><item><title><![CDATA[《统计学习方法》Chapter.3 k近邻法（KNN）]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/127369765</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/127369765</guid><author>weixin_45804601</author><pubDate>Mon, 17 Oct 2022 17:24:24 +0800</pubDate><description><![CDATA[统计学习方法(李航)第二版学习笔记，第三章k近邻法，原理+sklearn代码]]></description><category></category></item><item><title><![CDATA[sklearn.neighbors.KNeighborsClassifier函数详解]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/127369222</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/127369222</guid><author>weixin_45804601</author><pubDate>Mon, 17 Oct 2022 17:13:58 +0800</pubDate><description><![CDATA[【代码】sklearn.neighbors.KNeighborsClassifier函数详解。]]></description><category></category></item><item><title><![CDATA[sklearn.datasets.make_classification详解]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/127295649</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/127295649</guid><author>weixin_45804601</author><pubDate>Thu, 13 Oct 2022 09:59:19 +0800</pubDate><description><![CDATA[sklearn.datasets.make_classification详解]]></description><category></category></item><item><title><![CDATA[《统计学习方法》Chapter.2 感知机]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/127290553</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/127290553</guid><author>weixin_45804601</author><pubDate>Wed, 12 Oct 2022 20:57:44 +0800</pubDate><description><![CDATA[统计学习方法(李航)第二版学习笔记，第二章感知机，原理+sklearn代码]]></description><category></category></item><item><title><![CDATA[Sklearn中predict_proba函数用法及原理详解]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/127287406</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/127287406</guid><author>weixin_45804601</author><pubDate>Wed, 12 Oct 2022 17:42:15 +0800</pubDate><description><![CDATA[Sklearn中predict_proba函数用法及数学原理详解（以logistic回归为例）]]></description><category></category></item><item><title><![CDATA[sklearn.linear_model.Perceptron详解]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/127287339</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/127287339</guid><author>weixin_45804601</author><pubDate>Wed, 12 Oct 2022 17:39:30 +0800</pubDate><description><![CDATA[sklearn.linear_model.Perceptron详解]]></description><category></category></item><item><title><![CDATA[sklearn.preprocessing.StandardScaler详解]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/127280074</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/127280074</guid><author>weixin_45804601</author><pubDate>Wed, 12 Oct 2022 11:56:39 +0800</pubDate><description><![CDATA[sklearn.preprocessing.StandardScaler详解]]></description><category></category></item><item><title><![CDATA[sklearn train_test_split用法详解]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/127271024</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/127271024</guid><author>weixin_45804601</author><pubDate>Tue, 11 Oct 2022 20:31:03 +0800</pubDate><description><![CDATA[【代码】sklearn train_test_split用法详解。]]></description><category></category></item><item><title><![CDATA[Sklearn中的二分类模型可以进行多分类的原理]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/127268199</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/127268199</guid><author>weixin_45804601</author><pubDate>Tue, 11 Oct 2022 17:48:00 +0800</pubDate><description><![CDATA[介绍了Sklearn中的二分类模型可以进行多分类的原理，以及对one-vs-rest、one-vs-one、Error correcting output codes三种方法进行了详解]]></description><category></category></item><item><title><![CDATA[奇异值分解（SVD）C++实现]]></title><link>https://blog.youkuaiyun.com/weixin_45804601/article/details/125237191</link><guid>https://blog.youkuaiyun.com/weixin_45804601/article/details/125237191</guid><author>weixin_45804601</author><pubDate>Sat, 11 Jun 2022 21:11:54 +0800</pubDate><description><![CDATA[奇异值分解SVD（紧奇异值分解，截断奇异值分解）C++实现]]></description><category></category></item></channel></rss>