metya
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CoreML
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  <title>CoreML algorytms</title>
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    <h1>CoreML algorytms</h1>
    <h2>From the beginings to the not</h2>
    <p>metya<br/>Летняя Школа 2018, Deep Learning Workshop</p>
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  <article></article>  
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  <hgroup>
    <h1>A few base algorythms and even farther</h1>
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  <hgroup>
    <h1>Regression</h1>
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  <article data-timings="">
    <ul>
<li>Linear regression (<a href="https://habr.com/company/ods/blog/323890/">объяснение на хабре</a>)</li>
<li>NonLinear Regression</li>
<li>Descision Trees </li>
<li>Autoregression (ARIMA, etc.) </li>
</ul>

<p>(множественные модели, многомерные модели, регрессионные остатки)</p>

  </article>
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  <hgroup>
    <h1>Classification</h1>
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  <article data-timings="">
    <ul>
<li>Logistic regression (<a href="https://habr.com/company/ods/blog/323890/">объяснение на хабре</a>)</li>
<li>Descision Trees (<a href="https://habr.com/company/ods/blog/322534/">объяснение на хабре</a>)</li>
<li>K Nearest Neighbours (<a href="https://habr.com/company/ods/blog/322534/">объяснение на хабре</a>)</li>
<li>Naive Bayes (<a href="https://ru.wikipedia.org/wiki/%D0%A0%D1%9C%D0%A0%C2%B0%D0%A0%D1%91%D0%A0%D0%86%D0%A0%D0%85%D0%A1%E2%80%B9%D0%A0%E2%84%96_%D0%A0%C2%B1%D0%A0%C2%B0%D0%A0%E2%84%96%D0%A0%C2%B5%D0%A1%D0%83%D0%A0%D1%95%D0%A0%D0%86%D0%A1%D0%83%D0%A0%D1%94%D0%A0%D1%91%D0%A0%E2%84%96_%D0%A0%D1%94%D0%A0%C2%BB%D0%A0%C2%B0%D0%A1%D0%83%D0%A1%D0%83%D0%A0%D1%91%D0%A1%E2%80%9E%D0%A0%D1%91%D0%A0%D1%94%D0%A0%C2%B0%D0%A1%E2%80%9A%D0%A0%D1%95%D0%A1%D0%82">Wiki</a>, <a href="https://habr.com/post/415963/">habr (свежак!)</a>)</li>
<li>Linear discriminant analysis (Fisher&#39;s)</li>
<li>Support Vector Machine (<a href="https://habr.com/post/105220/">хабр</a>)</li>
<li>Genetics Algorithms</li>
<li>Expectation-Maximization (EM) (<a href="https://basegroup.ru/community/articles/em">где то в интернете</a>)</li>
</ul>

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    <h1>Clusterization</h1>
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  <article data-timings="">
    <p>(<a href="https://logic.pdmi.ras.ru/%7Esergey/teaching/mlau12/10-clustem.pdf">Николенко, слайды</a>, <a href="http://www.ccas.ru/voron/download/Clustering.pdf">воронцов, лекция</a>)</p>

<ul>
<li>K-means (<a href="https://habr.com/company/ods/blog/325654/">объяснение на хабре</a>)</li>
<li>DBSCAN (<a href="https://habrahabr.ru/post/322034/">хабр</a>)</li>
<li>Affinity Propagation (<a href="https://habr.com/post/321216/">habr</a>)</li>
<li>EM </li>
<li>Self-Organaized Maps aka Kohonen&#39;s networks (<a href="https://habr.com/post/338868/">все там же отличная статья!</a>)</li>
<li>Principal Component Analysis aka Понижение размерности (<a href="https://habr.com/company/ods/blog/325654/">объяснение на хабре</a>)</li>
<li>t-SNE </li>
</ul>

  </article>
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  <hgroup>
    <h1>Many of them together</h1>
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  <article data-timings="">
    <ul>
<li><p>Bagging aka Bootstrap aggregation (Random Forest, etc.) 
(<a href="https://habr.com/company/ods/blog/324402/">объяснение на хабре</a>)</p></li>
<li><p>Boosting (<a href="https://habr.com/company/ods/blog/327250/">все там же</a>, <a href="https://alexanderdyakonov.wordpress.com/2017/06/09/%D0%A0%D1%96%D0%A1%D0%82%D0%A0%C2%B0%D0%A0%D2%91%D0%A0%D1%91%D0%A0%C2%B5%D0%A0%D0%85%D0%A1%E2%80%9A%D0%A0%D0%85%D0%A1%E2%80%B9%D0%A0%E2%84%96-%D0%A0%C2%B1%D0%A1%D1%93%D0%A1%D0%83%D0%A1%E2%80%9A%D0%A0%D1%91%D0%A0%D0%85%D0%A0%D1%96/comment-page-1/">дьяконов</a>, <a href="http://www.machinelearning.ru/wiki/images/9/9a/fonarev.overview_of_boosting_methods.pdf">чья то неплохая курсовая</a>)</p></li>
</ul>

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  <hgroup>
    <h1>FIN!</h1>
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      <a href="#" target="_self" rel='tooltip' 
        data-slide=1 title='A few base algorythms and even farther'>
         1
      </a>
    </li>
    <li>
      <a href="#" target="_self" rel='tooltip' 
        data-slide=2 title='Regression'>
         2
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    <li>
      <a href="#" target="_self" rel='tooltip' 
        data-slide=3 title='Classification'>
         3
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      <a href="#" target="_self" rel='tooltip' 
        data-slide=4 title='Clusterization'>
         4
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      <a href="#" target="_self" rel='tooltip' 
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         5
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         6
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