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title: Home
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{% include cs60050_head.html %}

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    <h2>Overview</h2>
    <p>
      CS 60030 is a three credit running from
      July 18th through November 27, 2016.
    </p>
    <p>
      There are two important dates where the registrar is concerned:
    </p>
    <ul>
      <li> Last day to add: July 27th, 2016 </li>
      <li> Last day to drop: July 27th, 2016 </li>
    </ul>
    <p>
      The goal of this course is to provide you with a high-level introduction
      to the vast umbrella of learning algorithms, called Machine Learning.
      Starting from probabilistic approaches to pattern recognition, to
      the state-of-art neural network algorithms, the course aims to
      introduce and motivate the increasing relevance of Machine Learning
      algorithms from theoy to practice.
    </p>
    <p>
      As with any course, regardless of the subject, you do not really learn
      something until you sit down and try it out yourself.  The lecture and
      assignments are designed with this in mind &mdash; you should expect to learn
      the material by interacting with it directly.  The course material is
      designed assuming you have no prior experience developing of Machine
      Learning, but does assume knowledge of Probability and Statistic,
      Programming and Data Structures.  You are expected to put in an
      appropriate amount of effort to complete the assignments.
      Ultimately, what you put into the course is what
      you will get out of it.
    </p>
    <!-- <div class="media">
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        We gratefully acknowledge GitHub Education for an enabling the use
        of private repositories in support of this course.
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    <h2><a href="posts.html">Posts</a></h2>
    {% for post in site.posts limit:10 %}
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      <strong>{{ post.date | date_to_string }}</strong> &raquo;
        <a href="{{ post.url }}">{{ post.title }}</a>
        {{ post.excerpt }}
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    <a class="btn" href="posts.html">All posts &raquo;</a>
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