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(This article was first published on <strong><a href="http://www.win-vector.com/blog/2017/08/supervised-learning-in-r-regression/"> R – Win-Vector Blog</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>We are <em>very</em> excited to announce a new (paid) <a rel="nofollow" href="http://www.win-vector.com/" target="_blank">Win-Vector LLC</a> video training course: <a rel="nofollow" href="https://www.datacamp.com/courses/supervised-learning-in-r-regression?tap_a=5644-dce66f&tap_s=10907-287229" target="_blank">Supervised Learning in R: Regression</a> <a rel="nofollow" href="https://www.datacamp.com/courses/supervised-learning-in-r-regression?tap_a=5644-dce66f&tap_s=10907-287229" target="_blank">now available on DataCamp</a></p>
<p><a rel="nofollow" href="https://www.datacamp.com/courses/supervised-learning-in-r-regression?tap_a=5644-dce66f&tap_s=10907-287229" target="_blank"><img border="0" src="https://i1.wp.com/www.win-vector.com/blog/wp-content/uploads/2017/08/shield_image_course_3851_20170725-24872-3f982z.png?resize=271%2C271" alt="Shield image course 3851 20170725 24872 3f982z" title="shield_image_course_3851_20170725-24872-3f982z.png" data-recalc-dims="1"></a><span></span>The course is primarily authored by <a rel="nofollow" href="http://www.win-vector.com/site/staff/nina-zumel/" target="_blank">Dr. Nina Zumel</a> (our chief of course design) with contributions from <a rel="nofollow" href="http://www.win-vector.com/site/staff/john-mount/" target="_blank">Dr. John Mount</a>. This course will get you quickly up to speed covering:</p>
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<li>What <em>is</em> regression? (Hint: it is the art of making good numeric predictions, one of the most important tasks in data science, machine learning, or statistics.)</li>
<li>When does it work, and when does it not work?</li>
<li>How to move fluidly from basic ordinary least squares to Kaggle-winning methods such as gradient boosted trees.</li>
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<p>All of this is demonstrated using <a rel="nofollow" href="https://www.r-project.org/" target="_blank">R</a>, with many worked examples and exercises.</p>
<p>We worked very hard to make this course very much worth your time.</p>
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<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="http://www.win-vector.com/blog/2017/08/supervised-learning-in-r-regression/"> R – Win-Vector Blog</a></strong>.</div>
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