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(This article was first published on <strong><a href="http://mljar.com/blog/mljar-r-api/"> MLJAR Blog Category: R</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>Hi! We have added R API for mljar – so you can run sklearn, xgboost, lightGBM, Keras, RGF from one R line <img alt="🙂" src="https://s.w.org/images/core/emoji/2/72x72/1f642.png" class="wp-smiley"> Please check it on: <a rel="nofollow" href="https://github.com/mljar/mljar-api-R" target="_blank">https://github.com/mljar/mljar-api-R</a></p>
<p>A simple R wrapper for mljar.com API. It allows MLJAR users to create Machine Learning models with few lines of code:</p>
<p><img alt="enter image description here" src="https://i2.wp.com/s3.amazonaws.com/mljar-media/pics/mljar-R-snippet.png?w=456&ssl=1" data-recalc-dims="1"></p>
<p>That’s all folks! Yeah, I know, this makes Machine Learning super easy! You can use this code for following Machine Learning tasks:</p>
<ul>
<li>Binary classification (your target has only two unique values)</li>
<li>Regression (your target value is continuous)</li>
</ul>
<p>For more details please check our <a rel="nofollow" href="https://github.com/mljar/mljar-api-R" target="_blank">github</a>.</p>
<p>For more interesting R resources please check <a rel="nofollow" href="https://r-bloggers.com/" target="_blank">r-bloggers</a>.</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://mljar.com/blog/mljar-r-api/"> MLJAR Blog Category: R</a></strong>.</div>
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