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    I'm pretty sure there's a new scikit-learn blog-post about every
    day,<br>
    with highly varying quality. I don't think it's a good idea to spend
    our time reviewing them.<br>
    <br>
    <br>
    <div class="moz-cite-prefix">On 06/14/2017 04:43 PM, Vlad Niculae
      wrote:<br>
    </div>
    <blockquote type="cite"
cite="mid:CAFJw_eF6MxyThY7gqGVSJa8N+tjMzj946eqTJNQmRNiXJTt6NA@mail.gmail.com">
      <div dir="ltr">
        <div>Indeed, thank you, Gael!<br>
          <br>
          My 2c, not thought through very thoroughly, is that although a
          "related tutorials" would be great, it would be considerably
          more of a maintenance burden than scikit-learn-contrib,
          because docs go staler faster than code. We *could* force all
          code in the doc to be runnable and unit-tested, but that is
          probably not sufficient, because checking the text cannot
          really be done automatically. It would be great if we could
          figure out a system to enable community maintenance of related
          docs & tutorial without letting them go out of date, I
          think that's something we can think about.<br>
          <br>
        </div>
        <div>Yours,<br>
        </div>
        <div>Vlad<br>
        </div>
      </div>
      <div class="gmail_extra"><br>
        <div class="gmail_quote">On Wed, Jun 14, 2017 at 6:04 PM, Jacob
          Schreiber <span dir="ltr"><<a
              href="mailto:jmschreiber91@gmail.com" target="_blank"
              moz-do-not-send="true">jmschreiber91@gmail.com</a>></span>
          wrote:<br>
          <blockquote class="gmail_quote" style="margin:0 0 0
            .8ex;border-left:1px #ccc solid;padding-left:1ex">
            <div dir="ltr">Hi Gael
              <div><br>
              </div>
              <div>Thanks for the work! We are grateful for the work
                that other people do in providing these types of
                tutorials and introductions as they lower the barrier of
                entry for new people to get into machine learning. We
                generally don't include these in the official sklearn
                documentation, in no small part because it would be a
                time sink to decide from which among a large group of
                tutorials should be included. That being said, perhaps
                we should consider having a 'related tutorials' page
                similar to the 'related work' page, serving as an
                aggregation of links? </div>
              <div><br>
              </div>
              <div>Jacob</div>
            </div>
            <div class="gmail_extra"><br>
              <div class="gmail_quote">
                <div>
                  <div class="h5">On Mon, Jun 12, 2017 at 12:17 PM, Gaël
                    Pegliasco via scikit-learn <span dir="ltr"><<a
                        href="mailto:scikit-learn@python.org"
                        target="_blank" moz-do-not-send="true">scikit-learn@python.org</a>></span>
                    wrote:<br>
                  </div>
                </div>
                <blockquote class="gmail_quote" style="margin:0 0 0
                  .8ex;border-left:1px #ccc solid;padding-left:1ex">
                  <div>
                    <div class="h5">
                      <div text="#000000" bgcolor="#FFFFFF">
                        <p>Hi,</p>
                        <p>First of all, thanks to all contributors for
                          developping a such rich, simple, well
                          documented and easy to use machine learning
                          library for Python ; which, clearly, plays a
                          big role in Python world domination in AI !</p>
                        <p>As I'm using it more and more these past
                          month, I've written a french tutorial on
                          machine learning introduction: <br>
                        </p>
                        <ul>
                          <li>The Theory (no code here, only describing
                            AI with Python and machine learning concepts
                            with real examples):<br>
                            <a
                              class="m_8867072780432063741m_-1003972708457317367moz-txt-link-freetext"
href="https://makina-corpus.com/blog/metier/2017/initiation-au-machine-learning-avec-python-theorie"
                              target="_blank" moz-do-not-send="true">https://makina-corpus.com/blog<wbr>/metier/2017/initiation-au-<wbr>machine-learning-avec-python-<wbr>theorie</a></li>
                          <li>The Practice (using Scikit-Learn)<br>
                            <a
                              class="m_8867072780432063741m_-1003972708457317367moz-txt-link-freetext"
href="https://makina-corpus.com/blog/metier/2017/initiation-au-machine-learning-avec-python-pratique"
                              target="_blank" moz-do-not-send="true">https://makina-corpus.com/blog<wbr>/metier/2017/initiation-au-<wbr>machine-learning-avec-python-<wbr>pratique</a><br>
                            Another iris tutorial, but with much more
                            details than most I've read using this
                            database and using both supervised and
                            unsupervised learning<br>
                          </li>
                        </ul>
                        <p>I've received a few positive returns
                          regarding these 2 articles and others requests
                          to translate it into english.</p>
                        <p>I think that as to translate it into english,
                          you may find it useful to include it into
                          Scikit-Learn official documentation/examples ?</p>
                        <p>So, if you think it can be useful I could
                          work on it as soon as next week.</p>
                        <p>Anyway, any feedback is welcome, especially
                          because I'm not an expert and  that it may not
                          be error safe!<br>
                        </p>
                        <p>Thanks again for your great work and keep
                          going on !</p>
                        <span class="m_8867072780432063741HOEnZb"><font
                            color="#888888">
                            <p>Gaël,<br>
                            </p>
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                              class="m_8867072780432063741m_-1003972708457317367moz-signature">--
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      <pre wrap="">_______________________________________________
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