<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[Yukiice的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/Yukiice</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; Yukiice]]></copyright><item><title><![CDATA[在Linux服务器上升级Python版本]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/136637891</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/136637891</guid><author>Yukiice</author><pubDate>Mon, 11 Mar 2024 22:56:12 +0800</pubDate><description><![CDATA[近段时间在用导师给的服务器跑项目，所以升级了一下 Python 版本。这里分享下自己在升级 Python 时的流程和遇到的一些问题~]]></description><category></category></item><item><title><![CDATA[【机器学习】044_Kaggle房价预测（机器学习模型实战）]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/135002859</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/135002859</guid><author>Yukiice</author><pubDate>Sat, 16 Dec 2023 20:32:59 +0800</pubDate><description><![CDATA[【学习笔记】机器学习_044：通过Kaggle竞赛的房价预测实例，对机器学习模型的上手构建过程有了一个整体认知，对整个流程的代码部分也了解得更为充分。明晰了K则交叉验证这样的方法如何通过代码实际在模型构建中应用。]]></description><category></category></item><item><title><![CDATA[【机器学习】043_准确率、精确率、召回率]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/134982984</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/134982984</guid><author>Yukiice</author><pubDate>Wed, 13 Dec 2023 22:27:52 +0800</pubDate><description><![CDATA[【学习笔记】机器学习_043：明晰准确率、精确率、召回率的定义及表示，以浅显易懂的方式明确其含义。学习评估机器学习算法模型的又一指标。]]></description><category></category></item><item><title><![CDATA[【机器学习】042_迁移学习]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/134914665</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/134914665</guid><author>Yukiice</author><pubDate>Sun, 10 Dec 2023 22:18:08 +0800</pubDate><description><![CDATA[【学习笔记】机器学习_042：关于迁移学习进行相关学习。后续将针对深度学习中的迁移学习作进一步了解和学习。]]></description><category></category></item><item><title><![CDATA[【机器学习】041_模型开发迭代过程]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/134913487</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/134913487</guid><author>Yukiice</author><pubDate>Sun, 10 Dec 2023 21:16:32 +0800</pubDate><description><![CDATA[【学习笔记】机器学习_041：梳理模型开发迭代过程，对模型开发工程中的基本流程进行分析，并针对模型诊断、错误分析提供了一些注意点。]]></description><category></category></item><item><title><![CDATA[【机器学习】040_理解偏差与方差]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/134912509</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/134912509</guid><author>Yukiice</author><pubDate>Sun, 10 Dec 2023 20:02:18 +0800</pubDate><description><![CDATA[【学习笔记】机器学习_040：理解偏差与方差，理解学习曲线，认识解决高偏差与高方差的方法。]]></description><category></category></item><item><title><![CDATA[【机器学习】039_合理初始化]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/134521050</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/134521050</guid><author>Yukiice</author><pubDate>Tue, 21 Nov 2023 20:26:16 +0800</pubDate><description><![CDATA[【学习笔记】机器学习_039：学习了达到稳定训练所需的操作；为什么要合理初始化参数，以及合理初始化参数的方法。]]></description><category></category></item><item><title><![CDATA[【机器学习】038_梯度消失、梯度爆炸]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/134506347</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/134506347</guid><author>Yukiice</author><pubDate>Mon, 20 Nov 2023 23:02:46 +0800</pubDate><description><![CDATA[【学习笔记】机器学习_038：学习了梯度消失与梯度爆炸的原理，明确了两者可能带来的一些坏处。]]></description><category></category></item><item><title><![CDATA[【机器学习】037_暂退法]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/134497165</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/134497165</guid><author>Yukiice</author><pubDate>Mon, 20 Nov 2023 09:26:20 +0800</pubDate><description><![CDATA[【学习笔记】机器学习_037：学习了暂退法（丢弃法）的实现原理，理解了暂退法在模型构建中所体现出来的避免过拟合的作用。]]></description><category></category></item><item><title><![CDATA[【机器学习】036_权重衰退]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/134495838</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/134495838</guid><author>Yukiice</author><pubDate>Sun, 19 Nov 2023 22:34:02 +0800</pubDate><description><![CDATA[【学习笔记】机器学习_036：学习了正则化方法：权重衰退的相关知识]]></description><category></category></item><item><title><![CDATA[【机器学习】035_多层感知机Part.3_简洁实现多层感知机]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/134495248</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/134495248</guid><author>Yukiice</author><pubDate>Sun, 19 Nov 2023 20:43:26 +0800</pubDate><description><![CDATA[【学习笔记】机器学习_035：通过已有的函数库，用更简洁的代码实现简单的多层感知机模型。]]></description><category></category></item><item><title><![CDATA[【机器学习】034_多层感知机Part.2_从零实现多层感知机]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/134493557</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/134493557</guid><author>Yukiice</author><pubDate>Sun, 19 Nov 2023 20:41:31 +0800</pubDate><description><![CDATA[【学习笔记】机器学习_034：对多层感知机的实现原理有了进一步了解，编写代码实现了多层感知机。（其实现过程与softmax模型的区别并不大）]]></description><category></category></item><item><title><![CDATA[【机器学习】033_反向传播]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/134491591</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/134491591</guid><author>Yukiice</author><pubDate>Sun, 19 Nov 2023 18:08:30 +0800</pubDate><description><![CDATA[【学习笔记】机器学习_033：回顾了前向传播，学习了反向传播的原理；通过机器学习中的计算图理解反向传播；并使用Sympy自行求导]]></description><category></category></item><item><title><![CDATA[【机器学习】032_多种神经网络层类型]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/134433542</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/134433542</guid><author>Yukiice</author><pubDate>Sun, 19 Nov 2023 15:52:33 +0800</pubDate><description><![CDATA[【学习笔记】机器学习_032：初步了解卷积神经网络，知晓其组成与实现原理，以及卷积神经网络的优点与好处]]></description><category></category></item><item><title><![CDATA[【机器学习】031_Adam优化算法]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/134431187</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/134431187</guid><author>Yukiice</author><pubDate>Wed, 15 Nov 2023 23:09:44 +0800</pubDate><description><![CDATA[【学习笔记】机器学习_031：学习了梯度下降的一种优化算法：Adam算法的原理及实现]]></description><category></category></item><item><title><![CDATA[【机器学习】030_多层感知机Part.1_实现原理]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/134377540</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/134377540</guid><author>Yukiice</author><pubDate>Mon, 13 Nov 2023 23:53:50 +0800</pubDate><description><![CDATA[【学习笔记】机器学习_030：入了解了感知机的工作原理，作为一个处理二分类问题的模型而实现。]]></description><category></category></item><item><title><![CDATA[【机器学习】029_SoftMax模型Part.4_Softmax模型简洁实现]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/134366210</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/134366210</guid><author>Yukiice</author><pubDate>Sun, 12 Nov 2023 22:23:51 +0800</pubDate><description><![CDATA[【学习打卡】机器学习_029：对softmax模型利用库里已有的一些函数进行了简洁代码实现]]></description><category></category></item><item><title><![CDATA[【机器学习】028_SoftMax模型Part.3_从零实现Softmax模型]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/134275823</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/134275823</guid><author>Yukiice</author><pubDate>Sun, 12 Nov 2023 21:22:45 +0800</pubDate><description><![CDATA[【学习打卡】机器学习_028：回顾了Softmax模型的原理、知识点，从零开始编码实现了Softmax模型]]></description><category></category></item><item><title><![CDATA[【机器学习】027_激活函数]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/134222663</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/134222663</guid><author>Yukiice</author><pubDate>Mon, 06 Nov 2023 23:58:06 +0800</pubDate><description><![CDATA[【学习打卡】机器学习_027：学习了激活函数的有关知识，学习了三类最常用的激活函数，了解了激活函数的作用以及为什么要使用激活函数、如何选择激活函数等。]]></description><category></category></item><item><title><![CDATA[【机器学习】026_前向传播、代码搭建神经网络]]></title><link>https://blog.youkuaiyun.com/Yukiice/article/details/134206346</link><guid>https://blog.youkuaiyun.com/Yukiice/article/details/134206346</guid><author>Yukiice</author><pubDate>Fri, 03 Nov 2023 20:30:20 +0800</pubDate><description><![CDATA[【学习打卡】机器学习_026：学习了用实际代码表示神经网络的构建与前向传播的构建过程，学习了关键的计算单层输出激活值和连接不同层的函数实现]]></description><category></category></item></channel></rss>