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(This article was first published on <strong><a href="http://www.win-vector.com/blog/2017/08/thank-you-for-the-very-nice-comment/"> R – Win-Vector Blog</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>Somebody nice reached out and gave us this wonderful feedback on our new <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> (paid) video course.</p>
<blockquote><p>Thanks for a wonderful course on DataCamp on <code>XGBoost</code> and <code>Random forest</code>. I was struggling with <code>Xgboost</code> earlier and <code>Vtreat</code> has made my life easy now :).</p>
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<p><span></span><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> covers a <em>lot</em> as it treats predicting probabilities as a type of regression. Nina and I are very proud of this course and think it is very much worth your time (for the beginning through advanced <a rel="nofollow" href="https://www.r-project.org/" target="_blank"><code>R</code></a> user).</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></p>
<p><a rel="nofollow" href="https://winvector.github.io/vtreat/" target="_blank"><code>vtreat</code></a> is a statistically sound data cleaning and preparation tool introduced towards the end of the course. <code>R</code> users who try <code>vtreat</code> find it makes training and applying models <em>much</em> easier.</p>
<p><code>vtreat</code> is distributed as a free open-source package <a rel="nofollow" href="https://cran.r-project.org/package=vtreat" target="_blank">available on <code>CRAN</code></a>. If you are doing predictive modeling in <code>R</code> I honestly think you will find <code>vtreat</code> invaluable.</p>
<p><center><br>
<a rel="nofollow" href="https://winvector.github.io/vtreat/" target="_blank"><img border="0" alt="Vtreat" title="vtreat.png" src="https://i0.wp.com/www.win-vector.com/blog/wp-content/uploads/2017/08/vtreat.png?w=660" data-recalc-dims="1"></a><br>
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<p>And to the person who took the time to write the nice note. A sincere thank you from both Nina Zumel and myself. That kind of interaction really makes developing courses and packages feel worthwhile.</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/thank-you-for-the-very-nice-comment/"> R – Win-Vector Blog</a></strong>.</div>
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