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<div><b>Thank you</b> for the interesting session today - in
particular<b> to Metea and Peter</b> (<span style="color:
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background-color: rgb(255, 255, 255);
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initial; text-decoration-color: initial; display: inline
!important; float: none;">🍪</span><span style="color: rgb(32,
33, 36); font-family: arial, sans-serif; font-size: 16px;
font-style: normal; font-variant-ligatures: normal;
font-variant-caps: normal; font-weight: 400; letter-spacing:
normal; orphans: 2; text-align: left; text-indent: 0px;
text-transform: none; white-space: normal; widows: 2;
word-spacing: 0px; -webkit-text-stroke-width: 0px;
background-color: rgb(255, 255, 255);
text-decoration-thickness: initial; text-decoration-style:
initial; text-decoration-color: initial; display: inline
!important; float: none;">🍪</span><span style="color: rgb(32,
33, 36); font-family: arial, sans-serif; font-size: 16px;
font-style: normal; font-variant-ligatures: normal;
font-variant-caps: normal; font-weight: 400; letter-spacing:
normal; orphans: 2; text-align: left; text-indent: 0px;
text-transform: none; white-space: normal; widows: 2;
word-spacing: 0px; -webkit-text-stroke-width: 0px;
background-color: rgb(255, 255, 255);
text-decoration-thickness: initial; text-decoration-style:
initial; text-decoration-color: initial; display: inline
!important; float: none;">🍪</span><span style="color: rgb(32,
33, 36); font-family: arial, sans-serif; font-size: 16px;
font-style: normal; font-variant-ligatures: normal;
font-variant-caps: normal; font-weight: 400; letter-spacing:
normal; orphans: 2; text-align: left; text-indent: 0px;
text-transform: none; white-space: normal; widows: 2;
word-spacing: 0px; -webkit-text-stroke-width: 0px;
background-color: rgb(255, 255, 255);
text-decoration-thickness: initial; text-decoration-style:
initial; text-decoration-color: initial; display: inline
!important; float: none;"><span style="color: rgb(32, 33, 36);
font-family: arial, sans-serif; font-size: 16px; font-style:
normal; font-variant-ligatures: normal; font-variant-caps:
normal; font-weight: 400; letter-spacing: normal; orphans:
2; text-align: left; text-indent: 0px; text-transform: none;
white-space: normal; widows: 2; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255); text-decoration-thickness: initial;
text-decoration-style: initial; text-decoration-color:
initial; display: inline !important; float: none;"></span></span><span style="color: rgb(32, 33, 36); font-family: arial, sans-serif;
font-size: 16px; font-style: normal; font-variant-ligatures:
normal; font-variant-caps: normal; font-weight: 400;
letter-spacing: normal; orphans: 2; text-align: left;
text-indent: 0px; text-transform: none; white-space: normal;
widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px;
background-color: rgb(255, 255, 255);
text-decoration-thickness: initial; text-decoration-style:
initial; text-decoration-color: initial; display: inline
!important; float: none;">) </span>for enlightening us with
their presentations. In case you missed it or would like to
review some of the material, here is a list of sources used
today [1]. <br>
</div>
<div><br>
</div>
<div>The CAP annual meeting is next week, we might reschedule our
next Deep Learning gathering - a separate announcement will
follow.</div>
<div><br>
</div>
<div>Have a great weekend,</div>
<div> Eric</div>
<div><br>
</div>
<div>[1] <br>
</div>
<div>
<div>Notebook by Metea:<br>
</div>
<div><a class="moz-txt-link-freetext" href="https://drive.google.com/drive/folders/1gpbx8GLSBU-BqTxtflYQ1Sze_eadpxxQ?usp=sharing">https://drive.google.com/drive/folders/1gpbx8GLSBU-BqTxtflYQ1Sze_eadpxxQ?usp=sharing</a></div>
</div>
<div><br>
</div>
<div>Notebook used by Peter: In module 3.3 of<br>
</div>
<div><a href="https://www.edx.org/course/pytorch-basics-for-machine-learning">https://www.edx.org/course/pytorch-basics-for-machine-learning</a></div>
<div><br>
</div>
<div>Source with excellent gradient descent visualisations:<br>
</div>
<div><a class="moz-txt-link-freetext" href="https://www.tomasbeuzen.com/deep-learning-with-pytorch/README.html">https://www.tomasbeuzen.com/deep-learning-with-pytorch/README.html</a></div>
</div>
<div class="moz-cite-prefix"><br>
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<div class="moz-cite-prefix"><br>
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<div class="moz-cite-prefix">On 2021-06-04 7:57 a.m., Eric Drechsler
wrote:<br>
</div>
<blockquote type="cite" cite="mid:56805c21-e8a9-1e8c-3427-d2f1f42c4ed8@triumf.ca">
<div class="moz-cite-prefix">Kind reminder of our meeting in 5',
this Friday June <b>4th</b>. ;)<br>
</div>
<div class="moz-cite-prefix"><br>
</div>
<div class="moz-cite-prefix">On 2021-06-03 2:44 p.m., Eric
Drechsler wrote:<br>
</div>
<blockquote type="cite" cite="mid:7f7bf2320cbf4549a09f28106a1f143a@ITS-EXCHANGE04.sfu.ca">
Our meeting to review pyTorch basics will be held tomorrow
morning,<b> Friday June 3rd at 8am PST</b> in<br>
<p><a href="https://can01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fbluejeans.com%2F788204027&data=04%7C01%7Cedrechsler%40triumf.ca%7Cdf3d3b49c94b4e24da0808d92769152a%7Cc20535109cb34679a2d38f442e03b587%7C1%7C0%7C637584154560683561%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=az%2FZt35964dUjY%2ByM%2FXQdhJIHK7RYvL3i3WWjs9ZB%2F0%3D&reserved=0" originalsrc="https://bluejeans.com/788204027" shash="HRxuxDinGPB2zulhUiRYCvBsh5/9yGxd9koGsPMu7TF9Be1MZmduSgLnQn/K7/tlwm/44in+XYXD0KhrnGPBziBGOU7xgFm6dhKkK/cnYh3DQGok6QZWD1HRtC7bap2fT10pRRZhbr/AdedgIZ7OzBkQGhedWFgQ0/sISsSO1dw=" rev="en_rl_none" moz-do-not-send="true">https://bluejeans.com/788204027</a></p>
Metea and Peter kindly agreed to enlighten us. We are looking
forward to see you all!<br>
<br>
- Your DS Group<br>
<br>
<br>
<div class="moz-cite-prefix">On 2021-06-01 11:42 a.m., Eric
Drechsler wrote:<br>
</div>
<blockquote type="cite" cite="mid:3ca65eee-6831-3cb7-2539-4cae47f9a02e@triumf.ca">
<p>Hello aspiring pyTorch experts,<br>
<br>
the discussion in our last meeting revealed that many of you
would benefit from an overview of pyTorch basics first
before diving into the deep end. We are currently running a
doodle poll [1] to converge on a preferred meeting time.<br>
</p>
<p>We are still looking for volunteers to present a short,
informal summary of selected modules in the basics course
[2], which covers the following topics:<br>
<br>
Module 1: Tensors, Derivatives, Dataset<br>
Module 2: Linear Regression, Loss, Gradient Descent, Cost,
Training<br>
Module 3: Gradient Descent, Optimisation, Validation, early
stop<br>
Module 4: Linear Regression in depth: Prediction, multiple
outputs<br>
<br>
Digital glory and virtual cookies await! <span style="color: rgb(32, 33, 36); font-family: arial,
sans-serif; font-size: 16px; font-style: normal;
font-variant-ligatures: normal; font-variant-caps: normal;
font-weight: 400; letter-spacing: normal; orphans: 2;
text-align: left; text-indent: 0px; text-transform: none;
white-space: normal; widows: 2; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255); text-decoration-thickness: initial;
text-decoration-style: initial; text-decoration-color:
initial; display: inline !important; float: none;"> 🍪</span><br>
<br>
For more information, visit our slack channel.<br>
- Your DS Group<br>
</p>
<p>[1] <a class="moz-txt-link-freetext" href="https://can01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoodle.com%2Fpoll%2Fz3a2whmr9gpt8bp6%23calendar&data=04%7C01%7Cedrechsler%40triumf.ca%7Cdf3d3b49c94b4e24da0808d92769152a%7Cc20535109cb34679a2d38f442e03b587%7C1%7C0%7C637584154560683561%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=spgAzvKL95oLpz8L9WoUbddnaQw1oiHIEn6ri9K%2F1kM%3D&reserved=0" originalsrc="https://doodle.com/poll/z3a2whmr9gpt8bp6#calendar" shash="bqA801b0Fz1dY/vcQ8tu1Judx5HjlQaDjHNdHMQL7JwoDuk+797OwKeXa19lOOia99WFKnkzcXG+kANqEaraK8iGHZPraeJjy2l/Ry1EKFVUqeelI0bU5xSd0i/01AcPbHw5JTuLw5O3e50bwZ+futIFu6Cfbrr5OZzZRpNhGuw=" moz-do-not-send="true">
https://doodle.com/poll/z3a2whmr9gpt8bp6#calendar</a><br>
[2] <a class="moz-txt-link-freetext" href="https://can01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.edx.org%2Fcourse%2Fpytorch-basics-for-machine-learning&data=04%7C01%7Cedrechsler%40triumf.ca%7Cdf3d3b49c94b4e24da0808d92769152a%7Cc20535109cb34679a2d38f442e03b587%7C1%7C0%7C637584154560693553%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=sw9aIcMkcDFF4aH2nVLHoOSmlTKXpu0ICbpunV6py%2FE%3D&reserved=0" originalsrc="https://www.edx.org/course/pytorch-basics-for-machine-learning" shash="deixiS/KBpMhzRRpDun99B0ImckIPds56uJGudhyLxrSp5u1oI8Pj/63Pqf/EHBN649UA5sQbSAF2P2Kg559wV+vbEwlA+uuutVo5d1DpPahC92IzXWp8iKuejarSHa+AiHTWuzBlVOY8MgAX5p94e6NMWKvsUOw57AwNslE65E=" moz-do-not-send="true">
https://www.edx.org/course/pytorch-basics-for-machine-learning</a>
(choose the audit option for a free look at the course)<br>
</p>
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