<p>Machine learning is on-topic here at Cross Validated&mdash;see <a href="https://stats.stackexchange.com/help/on-topic">What topics can I ask about here?</a>, <a href="https://stats.meta.stackexchange.com/q/1577/17230">What is on topic on Cross Validated?</a>, <a href="https://stats.meta.stackexchange.com/q/492/17230">Are the “Machine Learning” questions on topic?</a>, &amp;
<a href="https://stats.meta.stackexchange.com/q/16/17230">Is machine learning a part of statistical analysis?</a> &amp; <a href="https://stats.meta.stackexchange.com/q/1057/17230">Should Machine Learning SE be merged with CrossValidated?</a>. That doesn't seem to have ever been contested. (It's interesting to note that a <a href="http://area51.stackexchange.com/proposals/26434/machine-learning">Machine Learning SE site</a> never took off, &amp; had to be merged with CV&mdash; see <a href="https://stats.meta.stackexchange.com/q/1061/17230">Incoming… Machine Learning Questions</a>.)</p>

<p>Though Data Science's <a href="https://datascience.stackexchange.com/help/on-topic">What topics can I ask about here?</a> isn't filled in yet, the tour page you link to &amp; the 500 questions with the <code>machine-learning</code> tag (which don't seem much different in general from machine learning questions on CV) suggest machine learning's also on-topic at DS. When it comes out of beta, and as the no. users increases, I'd expect what's on-topic to be defined more clearly, &amp; more narrowly.</p>

<p>So there's currently an overlap, but it's a little premature to decide what to do about it: whether it's tolerable, or whether machine learning questions should be migrated to one or the other site. Personally, I'd prefer them to stay here: at the least, there are many problems, techniques, &amp; theories that it'd be impossible to allocate exclusively to one of the disciplines of Machine Learning &amp; Statistics<sup>&dagger;</sup>; at the most, Machine Learning &amp; Statistics aren't two distinct disciplines but two cultures<sup>&ddagger;</sup> within the same discipline, between which we shouldn't be building artificial barriers.</p>

<p>&dagger; <a href="https://datascience.stackexchange.com/q/8381/3361">Your</a> "[...] Cross Validated (an ML reference) [...]" would come as a surprise to many statisticians.</p>

<p>&ddagger; <a href="http://projecteuclid.org/euclid.ss/1009213726" rel="nofollow noreferrer">Breiman (2001), "Statistical Modeling: The Two Cultures", <em>Statist. Sci.</em>, <strong>16</strong>, 3</a></p>
