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		<title>How is 0xdata&#8217;s H2O different from Apache Mahout ?</title>
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		<pubDate>Tue, 20 Jul 2021 03:15:13 +0000</pubDate>
				<category><![CDATA[Mahout]]></category>
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		<category><![CDATA[Advanced Apache Mahout Interview Questions]]></category>
		<category><![CDATA[Apache Mahout Essentials]]></category>
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		<category><![CDATA[Learning Apache Mahout Classification]]></category>
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					<description><![CDATA[Answer : By using H2O, you can use several of R, REST/JSON...]]></description>
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<h2 id="0xdatas-h2o-different-from-apache-mahout" class="color-purple" style="text-align: justify;">0xdata&#8217;s H2O different from Apache Mahout:</h2>
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<ul>
<li>By using H2O, you can use several of R, REST/JSON. For Example curl/bash, GUI browser, Scala or Java.</li>
<li>The H2O algorithms are usually 100x to 1000x faster than current Map/Reduce-based Mahout (but Mahout is working hard to port itself to both Spark and H2O).</li>
<li>H2O has some algorithms implemented:
<ol>
<li>Deep Learning / Neural Nets</li>
<li>Random Forest</li>
<li>Gradient Boosted Method</li>
<li>Generalized Linear Modelling including Logistic, Regression, Poisson, Gamma</li>
<li>PCA</li>
<li>KMeans (KMeans++, KMeans||, K-modes)</li>
<li>Naive Bayes</li>
<li>General Data Munging any standard R expression which auto-broadens to cover arrays also works the same in H2O.</li>
</ol>
</li>
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