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<!doctype html>
<!--[if lt IE 7]> <html class="no-js lt-ie9 lt-ie8 lt-ie7" lang=""> <![endif]-->
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<meta charset="utf-8">
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<title></title>
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<div class="header-container">
<header class="wrapper clearfix">
<div class="title"><img src="img/logo.png" alt="MSense"/></div>
<nav>
<ul>
<li><a href="#">Home</a></li>
<li><a href="#">Algorithms</a></li>
<li><a href="#">About</a></li>
</ul>
</nav>
</header>
</div>
<div class="main-container">
<div class="main wrapper clearfix">
<article>
<header>
<h1>Gradient Descent Algorithm</h1>
<p>Gradient descent is a first-order optimization algorithm. To find a local minimum of a function using gradient descent, one takes steps proportional to the negative of the gradient (or of the approximate gradient) of the function at the current point. If instead one takes steps proportional to the positive of the gradient, one approaches a local maximum of that function; the procedure is then known as gradient ascent.</p>
</header>
<section>
<h3>Choosing Data</h3>
<p> Now we should load input data for out machine learning algorithm. I suggest to use <a href="data/ex1data1.csv">data</a> from Andrew Ng's course assignment. Note: first row of data should be a title. After loading data press start button to run algo.
</p>
<input type="file" id="csv-file" name="files" class="peter-river-flat-button"/>
<button id="btn-calculate">Start!</button>
</section>
<footer>
<h3>Input data chart:</h3>
<div id="chart_div"></div>
</footer>
</article>
<aside>
<h3>aside</h3>
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