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On 13/01/16 18:30, Tennessee Leeuwenburg wrote:<br>
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cite="mid:CADhgxgcuDVfpsHPsQ5Twzkj75X6MJuNPQ87k8dh1txEKyknFjg@mail.gmail.com"
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<div dir="ltr">Hi all,
<div><br>
</div>
<div>I am running a tutorial on data science at LCA. The chief
language used will be Python, but users of other technologies
will still find the concepts relevant. In preparation for
this, I will be dusting off my slide deck, re-running the
code, and updating the content with a small amount of new
findings from the last 6 months. This is also an opportunity
to focus the content on what the LCA audience might be most
interested in.</div>
<div><br>
</div>
<div>Does anyone on this list have any particular questions
around data science / machine learning / AI which they would
like to see answered? </div>
<div><br>
</div>
<div>The session is practical, with supplied code and data, and
audience members should be able to re-create the results while
the session is being presented. Are there any particular
problems that people are confronted with? I might not be able
to re-work a major case study, but I should be able to
incorporate some relevant examples...</div>
<div><br>
</div>
<div>Cheers,</div>
<div>-T<br>
</div>
</div>
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<br>
Hi Tennessee,<br>
<br>
I won't be at LCA this year, but would love to see the slides/code
samples. Here are my suggestions, not having any real background in
data science:<br>
<ul>
<li>What's the difference between data science and computer
science? i.e. What are the important characteristics which
distinguish it as a field (or sub-field) in its own right?</li>
<li>My eyes tend to glaze over at the first sign of grade 12 or
higher maths (even though I did pretty well at it in grade 12).
What are the main mathematical concepts that non-data scientists
need to brush up on to understand what data scientists are
telling them?</li>
<li>Keen to hear anything you can teach about the theory behind
trending & anomaly detection, especially as it relates to
modern monitoring systems.<br>
</li>
</ul>
<p>Regards,<br>
Paul<br>
</p>
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