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	<title>机器学习 - 四号程序员</title>
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		<title>轻量化目标检测方案（移动端）</title>
		<link>https://www.coder4.com/archives/8191</link>
					<comments>https://www.coder4.com/archives/8191#respond</comments>
		
		<dc:creator><![CDATA[coder4]]></dc:creator>
		<pubDate>Wed, 11 Sep 2024 04:23:53 +0000</pubDate>
				<category><![CDATA[机器学习]]></category>
		<category><![CDATA[目标检测]]></category>
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					<description><![CDATA[yolov5-lite https://github.com/ppogg/YOLOv5-Lite 中端骁龙710G,能到10fps NanoDet-Plus https://github.com/RangiLyu/nanodet 中端骁龙710G,能到30fps 轻量级目标检测模型NanoDet-Plus微调、部署（保姆级教学） 实测误检、漏检比较多 YoloX https://github.com/Megvii-BaseDete[......] 继续阅读]]></description>
		
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		<title>[转]A Tour of Machine Learning Algorithms 机器学习算法回顾</title>
		<link>https://www.coder4.com/archives/4527</link>
					<comments>https://www.coder4.com/archives/4527#respond</comments>
		
		<dc:creator><![CDATA[coder4]]></dc:creator>
		<pubDate>Fri, 20 Mar 2015 15:21:35 +0000</pubDate>
				<category><![CDATA[机器学习]]></category>
		<category><![CDATA[算法]]></category>
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					<description><![CDATA[转载自：A Tour of Machine Learning Algorithms After we understand the type of machine learning problem we are working with, we can think about the type of data to collect and the types of machine learning algorithms we can try. In this post we take a to[......] 继续阅读]]></description>
		
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		<title>机器学习中Nomalize(规范化)和Standardize(标准化)</title>
		<link>https://www.coder4.com/archives/4394</link>
					<comments>https://www.coder4.com/archives/4394#respond</comments>
		
		<dc:creator><![CDATA[coder4]]></dc:creator>
		<pubDate>Mon, 26 Jan 2015 12:31:02 +0000</pubDate>
				<category><![CDATA[机器学习]]></category>
		<category><![CDATA[Nomalize]]></category>
		<category><![CDATA[Standardize]]></category>
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					<description><![CDATA[1. 标准化(Standardize)： 标准化给定数据集中所有数值属性(或者分别对每个feature列处理)的值到一个0均值和单位方差的正态分布。 2.规范化(Nomalize): 规范化给定数据集中的所有数值(或者分别对每个feature列处理)属性值，类属性除外。结果值默认在区间[0,1]，但是利用缩放和平移参数，我们能将数值属性值规范到任何区间。[......] 继续阅读]]></description>
		
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		<title>Mahout - Clustering (聚类篇)</title>
		<link>https://www.coder4.com/archives/4181</link>
					<comments>https://www.coder4.com/archives/4181#comments</comments>
		
		<dc:creator><![CDATA[coder4]]></dc:creator>
		<pubDate>Sat, 12 Apr 2014 13:31:39 +0000</pubDate>
				<category><![CDATA[大数据技术]]></category>
		<category><![CDATA[Hadoop]]></category>
		<category><![CDATA[Mahout]]></category>
		<category><![CDATA[数据挖掘]]></category>
		<category><![CDATA[机器学习]]></category>
		<category><![CDATA[聚类]]></category>
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					<description><![CDATA[什么是Mahout？ " Apache Mahout™ project's goal is to build a scalable machine learning library " 我来拓展一下： (1) Mahout 是Apache旗下的开源项目，集成了大量的机器学习算法。 (2) 大部分算法，可以运行在Hadoop上，具有很好的拓展性，使得大数据上的机器学习成为可能。 本篇主要探讨 Mahout 0.9 中的聚类(Clustering)工具的用法。 一、数据准[......] 继续阅读]]></description>
		
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