<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Machine-Learning on kangkun-lee blog</title><link>https://kangkun-lee.github.io/tags/machine-learning/</link><description>Recent content in Machine-Learning on kangkun-lee blog</description><generator>Hugo</generator><language>ko</language><lastBuildDate>Tue, 06 Jan 2026 11:04:00 +0900</lastBuildDate><atom:link href="https://kangkun-lee.github.io/tags/machine-learning/index.xml" rel="self" type="application/rss+xml"/><item><title>Machine Learning 이란</title><link>https://kangkun-lee.github.io/notes/machine-learning-%EC%9D%B4%EB%9E%80/</link><pubDate>Tue, 06 Jan 2026 11:04:00 +0900</pubDate><guid>https://kangkun-lee.github.io/notes/machine-learning-%EC%9D%B4%EB%9E%80/</guid><description>&lt;h1 id="machine-learning-이란"&gt;$Machine$ $Learning$ $이란$&lt;/h1&gt;
&lt;h2 id="machine-learning의-개념"&gt;Machine Learning의 개념&lt;/h2&gt;
&lt;p&gt;머신러닝(Machine Learning)은 &lt;strong&gt;명시적으로 규칙을 다 코딩하지 않아도&lt;/strong&gt;, 데이터를 통해 &lt;strong&gt;패턴(규칙)을 학습&lt;/strong&gt;해서 예측/분류/추천 같은 일을 하도록 만드는 방법이다.&lt;/p&gt;
&lt;p&gt;예를 들어,&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;“스팸 메일은 이런 단어가 많으면 스팸” 같은 규칙을 사람이 하나하나 만들기보다는,&lt;/li&gt;
&lt;li&gt;스팸/정상 메일 데이터를 많이 보여주고 &lt;strong&gt;스스로 기준을 찾게&lt;/strong&gt; 만드는 방식이다.&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;즉, 머신러닝은 이런 흐름으로 이해하면 된다.&lt;/p&gt;
&lt;ol&gt;
&lt;li&gt;데이터 수집&lt;/li&gt;
&lt;li&gt;특징(feature) 만들기&lt;/li&gt;
&lt;li&gt;모델(model)이 패턴 학습&lt;/li&gt;
&lt;li&gt;새로운 데이터에 대해 예측/판단&lt;/li&gt;
&lt;/ol&gt;
&lt;hr&gt;
&lt;h3 id="machine--learning"&gt;Machine + Learning&lt;/h3&gt;
&lt;h4 id="machine"&gt;$Machine$&lt;/h4&gt;
&lt;p&gt;여기서 Machine은 “기계”라기보다, &lt;strong&gt;학습을 수행하는 시스템&lt;/strong&gt;(프로그램/모델)을 말한다.&lt;/p&gt;</description></item><item><title>Linear Regression 의 의미</title><link>https://kangkun-lee.github.io/notes/linear-regression-%EC%9D%98-%EC%9D%98%EB%AF%B8/</link><pubDate>Wed, 31 Dec 2025 00:00:00 +0900</pubDate><guid>https://kangkun-lee.github.io/notes/linear-regression-%EC%9D%98-%EC%9D%98%EB%AF%B8/</guid><description>&lt;blockquote&gt;
&lt;h3 id="linear--regression"&gt;$Linear + Regression$&lt;/h3&gt;&lt;/blockquote&gt;
&lt;p&gt;&lt;svg viewBox="0 0 520 300" width="100%" height="300" xmlns="http://www.w3.org/2000/svg" role="img" aria-label="Linear Regression Chart"&gt;&lt;defs&gt;&lt;marker id="arrow" viewBox="0 0 10 10" refX="9" refY="5" markerWidth="6" markerHeight="6" orient="auto-start-reverse"&gt;&lt;path d="M 0 0 L 10 5 L 0 10 z" fill="currentColor"/&gt;&lt;/marker&gt;&lt;/defs&gt;&lt;g stroke="currentColor" stroke-opacity="0.1" stroke-width="1"&gt;&lt;line x1="40" y1="50" x2="500" y2="50"/&gt;&lt;line x1="40" y1="100" x2="500" y2="100"/&gt;&lt;line x1="40" y1="150" x2="500" y2="150"/&gt;&lt;line x1="40" y1="200" x2="500" y2="200"/&gt;&lt;line x1="100" y1="20" x2="100" y2="250"/&gt;&lt;line x1="200" y1="20" x2="200" y2="250"/&gt;&lt;line x1="300" y1="20" x2="300" y2="250"/&gt;&lt;line x1="400" y1="20" x2="400" y2="250"/&gt;&lt;/g&gt;&lt;line x1="40" y1="250" x2="500" y2="250" stroke="currentColor" stroke-width="2" marker-end="url(#arrow)"/&gt;&lt;line x1="40" y1="250" x2="40" y2="20" stroke="currentColor" stroke-width="2" marker-end="url(#arrow)"/&gt;&lt;g stroke="currentColor" stroke-width="1" stroke-dasharray="4,2" opacity="0.6"&gt;&lt;line x1="90" y1="170" x2="90" y2="180"/&gt;&lt;line x1="160" y1="150" x2="160" y2="155"/&gt;&lt;line x1="240" y1="120" x2="240" y2="130"/&gt;&lt;line x1="320" y1="95" x2="320" y2="105"/&gt;&lt;line x1="420" y1="70" x2="420" y2="75"/&gt;&lt;/g&gt;&lt;line x1="40" y1="195" x2="480" y2="55" stroke="currentColor" stroke-width="2.5"/&gt;&lt;g fill="currentColor" stroke="currentColor" stroke-width="1" fill-opacity="0.7"&gt;&lt;circle cx="90" cy="170" r="4"/&gt;&lt;circle cx="160" cy="150" r="4"/&gt;&lt;circle cx="240" cy="120" r="4"/&gt;&lt;circle cx="320" cy="95" r="4"/&gt;&lt;circle cx="420" cy="70" r="4"/&gt;&lt;/g&gt;&lt;text x="490" y="275" font-family="Times New Roman, serif" font-style="italic" font-size="16" fill="currentColor"&gt;x&lt;/text&gt;&lt;text x="10" y="30" font-family="Times New Roman, serif" font-style="italic" font-size="16" fill="currentColor"&gt;y&lt;/text&gt;&lt;text x="380" y="50" font-family="Times New Roman, serif" font-size="14" fill="currentColor"&gt;ŷ = β₀ + β₁x&lt;/text&gt;&lt;/svg&gt;&lt;/p&gt;</description></item></channel></rss>