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DL(1) 작성중
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{% include group-by-array collection=site.posts field="categories" %}
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{% for category in group_names %}
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{% assign posts = group_items[forloop.index0] %}
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<h2 id="{{ category | slugify }}" class="archive__subtitle">{{ category }}</h2>
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{% for post in posts %}
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title: "Posts by Tag"
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{% capture site_tags %}{% for tag in site.tags %}{{ tag | first }}{% unless forloop.last %},{% endunless %}{% endfor %}{% endcapture %}
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<!-- site_tags: {{ site_tags }} -->
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{% assign tag_words = site_tags | split:',' | sort %}
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<div id="tags">
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<ul class="tag-box inline">
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{% for item in (0..site.tags.size) %}{% unless forloop.last %}
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{% capture this_word %}{{ tag_words[item] | strip_newlines }}{% endcapture %}
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<li< 57AE /span>><a href="#{{ this_word | cgi_escape }}">{{ this_word }} <span>{{ site.tags[this_word].size }}</span></a></li>
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{% for item in (0..site.tags.size) %}{% unless forloop.last %}
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<h2 id="{{ this_word | cgi_escape }}">{{ this_word }}</h2>
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<time datetime="{{ post.date | date_to_xmlschema }}" itemprop="datePublished">{{ post.date | date: "%b %d, %Y" }}</time>
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<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="3.8.5">Jekyll</generator><link href="http://localhost:4000/feed.xml" rel="self" type="application/atom+xml" /><link href="http://localhost:4000/" rel="alternate" type="text/html" /><updated>2019-11-14T18:18:40+09:00</updated><id>http://localhost:4000/feed.xml</id><title type="html">MIOS Code</title><subtitle>MIOS Codes and Thinks</subtitle><author><name>MIOS</name><email>ijanamilot@gmail.com</email></author><entry><title type="html">딥러닝(1) - 개요, 퍼셉트론</title><link href="http://localhost:4000/deep%20learning/2019/11/14/DL(1)/" rel="alternate" type="text/html" title="딥러닝(1) - 개요, 퍼셉트론" /><published>2019-11-14T00:00:00+09:00</published><updated>2019-11-14T00:00:00+09:00</updated><id>http://localhost:4000/deep%20learning/2019/11/14/DL(1)</id><content type="html" xml:base="http://localhost:4000/deep%20learning/2019/11/14/DL(1)/">&lt;ul id=&quot;markdown-toc&quot;&gt;
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&lt;li&gt;&lt;a href=&quot;#1-ai-dl-ml--neural-network&quot; id=&quot;markdown-toc-1-ai-dl-ml--neural-network&quot;&gt;1. AI, DL, ML … Neural Network&lt;/a&gt; &lt;ul&gt;
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&lt;li&gt;&lt;a href=&quot;#인공지능ai의-역사&quot; id=&quot;markdown-toc-인공지능ai의-역사&quot;&gt;인공지능(AI)의 역사&lt;/a&gt;&lt;/li&gt;
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&lt;li&gt;&lt;a href=&quot;#deep-learning-machine-learning&quot; id=&quot;markdown-toc-deep-learning-machine-learning&quot;&gt;Deep Learning (Machine Learning)&lt;/a&gt;&lt;/li&gt;
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&lt;/ul&gt;
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&lt;/li&gt;
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&lt;li&gt;&lt;a href=&quot;#2-perceptron&quot; id=&quot;markdown-toc-2-perceptron&quot;&gt;2. Perceptron&lt;/a&gt; &lt;ul&gt;
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<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="3.8.5">Jekyll</generator><link href="http://localhost:4000/feed.xml" rel="self" type="application/atom+xml" /><link href="http://localhost:4000/" rel="alternate" type="text/html" /><updated>2019-11-14T19:46:22+09:00</updated><id>http://localhost:4000/feed.xml</id><title type="html">MIOS Code</title><subtitle>MIOS Codes and Thinks</subtitle><author><name>MIOS</name><email>ijanamilot@gmail.com</email></author><entry><title type="html">(DL) MySQL Dump ERROR</title><link href="http://localhost:4000/mysql%20workbench/2019/11/14/DL(1)-perceptron/" rel="alternate" type="text/html" title="(DL) MySQL Dump ERROR" /><published>2019-11-14T00:00:00+09:00</published><updated>2019-11-14T00:00:00+09:00</updated><id>http://localhost:4000/mysql%20workbench/2019/11/14/DL(1)-perceptron</id><content type="html" xml:base="http://localhost:4000/mysql%20workbench/2019/11/14/DL(1)-perceptron/">&lt;ul id=&quot;markdown-toc&quot;&gt;
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&lt;li&gt;&lt;a href=&quot;#1-퍼셉트론&quot; id=&quot;markdown-toc-1-퍼셉트론&quot;&gt;1. 퍼셉트론&lt;/a&gt; &lt;ul&gt;
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&lt;li&gt;&lt;a href=&quot;#개념&quot; id=&quot;markdown-toc-개념&quot;&gt;개념&lt;/a&gt;&lt;/li&gt;
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&lt;li&gt;&lt;a href=&quot;#학습방법&quot; id=&quot;markdown-toc-학습방법&quot;&gt;학습방법&lt;/a&gt;&lt;/li&gt;
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&lt;li&gt;&lt;a href=&quot;#선형분류&quot; id=&quot;markdown-toc-선형분류&quot;&gt;선형분류&lt;/a&gt;&lt;/li&gt;
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&lt;/li&gt;
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&lt;li&gt;&lt;a href=&quot;#오차-역전파-error-backpropagatin&quot; id=&quot;markdown-toc-오차-역전파-error-backpropagatin&quot;&gt;오차 역전파 (Error Backpropagatin)&lt;/a&gt; &lt;ul&gt;
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&lt;li&gt;&lt;a href=&quot;#reference&quot; id=&quot;markdown-toc-reference&quot;&gt;Reference&lt;/a&gt;&lt;/li&gt;
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&lt;/ul&gt;
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&lt;/li&gt;
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&lt;li&gt;&lt;a href=&quot;#오차-역전파-error-backpropagatin&quot; id=&quot;markdown-toc-오차-역전파-error-backpropagatin&quot;&gt;오차 역전파 (Error Backpropagatin)&lt;/a&gt;&lt;/li&gt;
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&lt;h1 id=&quot;1-ai-dl-ml--neural-network&quot;&gt;1. AI, DL, ML … Neural Network&lt;/h1&gt;
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&lt;h2 id=&quot;인공지능ai의-역사&quot;&gt;인공지능(AI)의 역사&lt;/h2&gt;
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&lt;ul&gt;
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&lt;li&gt;1943년: 최초 신경망 모델 제안&lt;/li&gt;
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&lt;li&gt;1950년: 앨런 튜링이 튜링 테스트 제안&lt;/li&gt;
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&lt;li&gt;(첫 번째 AI 붐) 1950년대 후반 ~ 1970년대 전반
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&lt;ul&gt;
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&lt;li&gt;1956년 : 미국 다트머스의 학회에서 AI 이란 용어 처음 사용&lt;/li&gt;
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&lt;li&gt;1957년 : 코넬 항공 연구소 프랑크 로젠이 Perceptron 고안&lt;/li&gt;
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&lt;/ul&gt;
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&lt;/li&gt;
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&lt;li&gt;(두 번째 AI 붐) 1980년대: 주로 컴퓨터가 자율적으로 배우고 결정하는 종류가 아닌 인간으로부터 지식을 얻음&lt;/li&gt;
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&lt;li&gt;1990년대: 세계 체스 챔피언을 물리 친 AI&lt;/li&gt;
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&lt;li&gt;(세 번째 AI 붐) 2010년대: 딥 러닝 (머신 러닝)이라는 새로운 기술이 각광&lt;/li&gt;
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&lt;/ul&gt;
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&lt;center&gt;&lt;img src=&quot;https://mioscode.github.io/assets/images/history.jpg&quot; width=&quot;80%&quot; /&gt;&lt;/center&gt;
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&lt;h2 id=&quot;deep-learning-machine-learning&quot;&gt;Deep Learning (Machine Learning)&lt;/h2&gt;
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&lt;ul&gt;
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&lt;li&gt;딥 러닝은 최신 인공 신경망(Artificial neural network) 기술로 인간 두뇌의 메커니즘을 시뮬레이션&lt;/li&gt;
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&lt;li&gt;인간의 뇌는 정보를 전달하기 위해 뉴런(neuron)과 뉴런들을 연결하는 시냅스(synapse)로 구성&lt;/li&gt;
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&lt;li&gt;인공 신경망(또는 단순히 신경망이라고 함)은 이러한 뉴런과 시냅스를 모델링&lt;/li&gt;
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&lt;li&gt;이 모델은 두 번째 AI 붐 중에 적극적으로 연구되었지만 레이어 매우 작았고, 이후 기술 발전으로 인해 대규모 네트워크로 확장되어 컴퓨터가 심층 학습을 실행할 수 있게됨&lt;/li&gt;
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&lt;/ul&gt;
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&lt;center&gt;&lt;img src=&quot;https://mioscode.github.io/assets/images/neural_network.jpg&quot; width=&quot;80%&quot; /&gt;&lt;/center&gt;
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&lt;h1 id=&quot;2-perceptron&quot;&gt;2. Perceptron&lt;/h1&gt;
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&lt;h1 id=&quot;1-퍼셉트론&quot;&gt;1. 퍼셉트론&lt;/h1&gt;
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&lt;h2 id=&quot;개념&quot;&gt;개념&lt;/h2&gt;
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&lt;p&gt;&lt;img src=&quot;/Users/somi.han/Documents/Deep%20Learning/lecture-29-convolutional-neural-networks-computer-vision-spring2015-9-638.jpg&quot; alt=&quot;&quot; /&gt;&lt;/p&gt;
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&lt;li&gt;1957년에 코넬 항공 연구소(Cornell Aeronautical Lab)의 프랑크 로젠블라트(Frank Rosenblatt)에 의해 고안&lt;/li&gt;
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&lt;li&gt;1957년, Rosenblatt이 뉴런(neuron)을 모방 하여 고안&lt;/li&gt;
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&lt;li&gt;뉴런: 특정 자극(impulse) 이 있다면 그 자극이 어느 역치(threshold) 이상이여야 반응(activation)
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&lt;li&gt;활동전위(action potential)가 축삭(axon)을 따라 내려가면서 세포막 안팎의 극성이 변화 -&amp;gt; 다른 뉴런에서 온 신호에 반응하여 막이 역치(threshold) 전위에 도달하면 Na+ 및 K+ 개폐 이온 채널이 여닫힘 -&amp;gt; 활동전위가 시작될 때 Na+ 채널이 열리고 Na+가 축삭 안으로 들어와 탈분극(Depolarization), 재분극은 K+ 채널이 열리고 K+가 축삭 밖으로 나갈 때 일어남 -&amp;gt; 채널의 개폐로 세포 안팎 극성이 변화 -&amp;gt; 신경 자극은 한 방향으로만 이동하여 축삭 말단(axon ending)에서 다른 뉴런으로 신호를 전달&lt;/li&gt;
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&lt;center&gt;&lt;img src=&quot;https://mioscode.github.io/assets/images/action_potential.png&quot; width=&quot;80%&quot; /&gt;&lt;/center&gt;
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(출처: 위키)
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&lt;/li&gt;
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&lt;li&gt;퍼셉트론: 입력(input) 신호의 총합이 정해진 임계값($\theta$) 넘었을 때 $1$을 출력(output), 넘지 못하면 $0$ 또는 $-1$ 출력&lt;/li&gt;
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&lt;li&gt;1957년 고안, neuron 본뜸&lt;/li&gt;
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&lt;li&gt;입력 신호의 총합이 정해진 임계값(세타θ, neuron: threshold) 넘었을 때 1을 출력(neuron: activation), 넘지 못하면 0 또는 -1 출력&lt;/li&gt;
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&lt;p&gt;각 입력신호에 고유한 weight 부여되며 기계학습은 이 weight(입력을 조절하니 매개변수로도 볼 수 있음)의 값을 정하는 작업
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&lt;li&gt;epoch를 늘릴 수록 가중치가 계속 업데이트(학습)되면서 점점 오차가 줄어나가는 방법&lt;/li&gt;
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&lt;p&gt;&lt;img src=&quot;/Users/somi.han/Documents/Deep%20Learning/997C7A3359EEF5CA1F.png&quot; alt=&quot;&quot; /&gt;&lt;/p&gt;
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&lt;h2 id=&quot;reference&quot;&gt;Reference&lt;/h2&gt;
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&lt;p&gt;https://journal.jp.fujitsu.com/en/2016/02/09/01/
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https://sacko.tistory.com/10?category=632408
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https://www.neuraldesigner.com/blog/perceptron-the-main-component-of-neural-networks&lt;/p&gt;</content><author><name>MIOS</name><email>ijanamilot@gmail.com</email></author><category term="Perceptron" /><category term="Deep Learning" /><summary type="html"></summary></entry><entry><title type="html">(MySQL Workbench) MySQL Dump ERROR</title><link href="http://localhost:4000/mysql%20workbench/2019/11/12/mysqlworkbench-mysqldump-error/" rel="alternate" type="text/html" title="(MySQL Workbench) MySQL Dump ERROR" /><published>2019-11-12T00:00:00+09:00</published><updated>2019-11-12T00:00:00+09:00</updated><id>http://localhost:4000/mysql%20workbench/2019/11/12/mysqlworkbench-mysqldump-error</id><content type="html" xml:base="http://localhost:4000/mysql%20workbench/2019/11/12/mysqlworkbench-mysqldump-error/">&lt;h1 id=&quot;mysql-workbench---mysql-dump-error&quot;&gt;MySQL Workbench - MySQL Dump ERROR&lt;/h1&gt;
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&lt;p&gt;&lt;img src=&quot;/Users/somi.han/Documents/Deep%20Learning/997C7A3359EEF5CA1F.png&quot; alt=&quot;&quot; /&gt;&lt;/p&gt;</content><author><name>MIOS</name><email>ijanamilot@gmail.com</email></author><category term="MySQL" /><category term="mysqldump" /><summary type="html"></summary></entry><entry><title type="html">(MySQL Workbench) MySQL Dump ERROR</title><link href="http://localhost:4000/mysql%20workbench/2019/11/12/mysqlworkbench-mysqldump-error/" rel="alternate" type="text/html" title="(MySQL Workbench) MySQL Dump ERROR" /><published>2019-11-12T00:00:00+09:00</published><updated>2019-11-12T00:00:00+09:00</updated><id>http://localhost:4000/mysql%20workbench/2019/11/12/mysqlworkbench-mysqldump-error</id><content type="html" xml:base="http://localhost:4000/mysql%20workbench/2019/11/12/mysqlworkbench-mysqldump-error/">&lt;h1 id=&quot;mysql-workbench---mysql-dump-error&quot;&gt;MySQL Workbench - MySQL Dump ERROR&lt;/h1&gt;
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&lt;h2 id=&quot;내용&quot;&gt;내용&lt;/h2&gt;
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&lt;p&gt;MySQL Workbench에서 Data Export 시,
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<a href="/deep%20learning/2019/11/14/DL(1)/" rel="permalink">딥러닝(1) - 개요, 퍼셉트론
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