fix URL, formatting

- hyperlinks in How to X - bullets in Meetings
JRaviLab · Mar 6, 2024 · 84a8eeb · epbrenner · Mar 8, 2024 · 84a8eeb
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diff --git a/docs/howto.html b/docs/howto.html
@@ -174,7 +174,7 @@ <h1 class="quarto-secondary-nav-title"><span class="chapter-number">3</span>&nbs
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="./career-dev.html" class="sidebar-item-text sidebar-link"><span class="chapter-number">G</span>&nbsp; <span class="chapter-title">Career/Professional Development Week</span></a>
+  <a href="./career-dev.html" class="sidebar-item-text sidebar-link"><span class="chapter-number">G</span>&nbsp; <span class="chapter-title">Career/Professional Development</span></a>
   </div>
 </li>
       </ul>
@@ -251,20 +251,20 @@ <h2 data-number="3.3" class="anchored" data-anchor-id="helpful-links-to-learn-mo
 <ul>
 <li>YouTube Videos
 <ul>
-<li>[Machine Learning from Scratch by AssemblyAI] (https://www.youtube.com/watch?v=p1hGz0w_OCo&amp;list=PLcWfeUsAys2k_xub3mHks85sBHZvg24Jd)</li>
-<li>[MIT Deep Learning Course] (http://introtodeeplearning.com/)</li>
-<li>[Deep Learning by Assembly AI] (https://www.youtube.com/watch?v=dccdadl90vs&amp;list=PLcWfeUsAys2nPgh-gYRlexc6xvscdvHqX)</li>
-<li>[Understanding Tensors by Dan Fleisch] (https://www.youtube.com/watch?v=f5liqUk0ZTw)</li>
-<li>[Understanding Neural Networks] (https://www.youtube.com/watch?v=aircAruvnKk)</li>
-<li>[Basic Computer Parts Explained] (https://www.youtube.com/watch?v=ExxFxD4OSZ0)</li>
+<li><a href="https://www.youtube.com/watch?v=p1hGz0w_OCo&amp;list=PLcWfeUsAys2k_xub3mHks85sBHZvg24Jd">Machine Learning from Scratch by AssemblyAI</a></li>
+<li><a href="http://introtodeeplearning.com/">MIT Deep Learning Course</a></li>
+<li><a href="https://www.youtube.com/watch?v=dccdadl90vs&amp;list=PLcWfeUsAys2nPgh-gYRlexc6xvscdvHqX">Deep Learning by Assembly AI</a></li>
+<li><a href="https://www.youtube.com/watch?v=f5liqUk0ZTw">Understanding Tensors by Dan Fleisch</a></li>
+<li><a href="https://www.youtube.com/watch?v=aircAruvnKk">Understanding Neural Networks</a></li>
+<li><a href="https://www.youtube.com/watch?v=ExxFxD4OSZ0">Basic Computer Parts Explained</a></li>
 </ul></li>
 <li>Articles:
 <ul>
-<li>[Transformers] (http://jalammar.github.io/illustrated-transformer/)</li>
+<li><a href="http://jalammar.github.io/illustrated-transformer/">Transformers</a></li>
 </ul></li>
 <li>Coding Practice Sites
 <ul>
-<li>[LeetCode] (https://leetcode.com/)</li>
+<li><a href="https://leetcode.com/">LeetCode</a></li>
 </ul></li>
 </ul>
 <p>📌 Go-to books (also in pinned posts on Slack)</p>

diff --git a/docs/search.json b/docs/search.json
@@ -95,7 +95,7 @@
     "href": "howto.html#helpful-links-to-learn-more-about-machine-learning",
     "title": "3  How to X",
     "section": "3.3 Helpful Links to learn more about Machine Learning",
-    "text": "3.3 Helpful Links to learn more about Machine Learning\n\nYouTube Videos\n\n[Machine Learning from Scratch by AssemblyAI] (https://www.youtube.com/watch?v=p1hGz0w_OCo&list=PLcWfeUsAys2k_xub3mHks85sBHZvg24Jd)\n[MIT Deep Learning Course] (http://introtodeeplearning.com/)\n[Deep Learning by Assembly AI] (https://www.youtube.com/watch?v=dccdadl90vs&list=PLcWfeUsAys2nPgh-gYRlexc6xvscdvHqX)\n[Understanding Tensors by Dan Fleisch] (https://www.youtube.com/watch?v=f5liqUk0ZTw)\n[Understanding Neural Networks] (https://www.youtube.com/watch?v=aircAruvnKk)\n[Basic Computer Parts Explained] (https://www.youtube.com/watch?v=ExxFxD4OSZ0)\n\nArticles:\n\n[Transformers] (http://jalammar.github.io/illustrated-transformer/)\n\nCoding Practice Sites\n\n[LeetCode] (https://leetcode.com/)\n\n\n📌 Go-to books (also in pinned posts on Slack)\n\nR for Data Science (for tidyverse and such)\nHands-On Programming with R (for base R) Intro to Git, GitHub resources"
+    "text": "3.3 Helpful Links to learn more about Machine Learning\n\nYouTube Videos\n\nMachine Learning from Scratch by AssemblyAI\nMIT Deep Learning Course\nDeep Learning by Assembly AI\nUnderstanding Tensors by Dan Fleisch\nUnderstanding Neural Networks\nBasic Computer Parts Explained\n\nArticles:\n\nTransformers\n\nCoding Practice Sites\n\nLeetCode\n\n\n📌 Go-to books (also in pinned posts on Slack)\n\nR for Data Science (for tidyverse and such)\nHands-On Programming with R (for base R) Intro to Git, GitHub resources"
   },
   {
     "objectID": "howto.html#use-vpn",

diff --git a/howto.qmd b/howto.qmd
@@ -25,16 +25,16 @@ A couple of helpful GitHub repositories - <https://github.com/jananiravi/worksho
 ## Helpful Links to learn more about Machine Learning
 
 -   YouTube Videos
-    -   \[Machine Learning from Scratch by AssemblyAI\] (https://www.youtube.com/watch?v=p1hGz0w_OCo&list=PLcWfeUsAys2k_xub3mHks85sBHZvg24Jd)
-    -   \[MIT Deep Learning Course\] (http://introtodeeplearning.com/)
-    -   \[Deep Learning by Assembly AI\] (https://www.youtube.com/watch?v=dccdadl90vs&list=PLcWfeUsAys2nPgh-gYRlexc6xvscdvHqX)
-    -   \[Understanding Tensors by Dan Fleisch\] (https://www.youtube.com/watch?v=f5liqUk0ZTw)
-    -   \[Understanding Neural Networks\] (https://www.youtube.com/watch?v=aircAruvnKk)
-    -   \[Basic Computer Parts Explained\] (https://www.youtube.com/watch?v=ExxFxD4OSZ0)
+    -   [Machine Learning from Scratch by AssemblyAI](https://www.youtube.com/watch?v=p1hGz0w_OCo&list=PLcWfeUsAys2k_xub3mHks85sBHZvg24Jd)
+    -   [MIT Deep Learning Course](http://introtodeeplearning.com/)
+    -   [Deep Learning by Assembly AI](https://www.youtube.com/watch?v=dccdadl90vs&list=PLcWfeUsAys2nPgh-gYRlexc6xvscdvHqX)
+    -   [Understanding Tensors by Dan Fleisch](https://www.youtube.com/watch?v=f5liqUk0ZTw)
+    -   [Understanding Neural Networks](https://www.youtube.com/watch?v=aircAruvnKk)
+    -   [Basic Computer Parts Explained](https://www.youtube.com/watch?v=ExxFxD4OSZ0)
 -   Articles:
-    -   \[Transformers\] (http://jalammar.github.io/illustrated-transformer/)
+    -   [Transformers](http://jalammar.github.io/illustrated-transformer/)
 -   Coding Practice Sites
-    -   \[LeetCode\] (https://leetcode.com/)
+    -   [LeetCode](https://leetcode.com/)
 
 📌 Go-to books (also in pinned posts on Slack)
 

diff --git a/meetings.qmd b/meetings.qmd
@@ -18,12 +18,24 @@ Please update this semester's meeting schedule [here](https://docs.google.com/sp
 
 ### Journal clubs & Primers
 
-[Sign up here](https://docs.google.com/spreadsheets/d/14919WwHIiKFFBcYZgF9wxACIYqh-gW-2QeDyM4WU28E/edit#gid=943003305) **Journal clubs** <br> - Journal club serves as opportunities to present interesting new research papers from other groups. For journal clubs, all members of the lab must read the selected paper ahead of time and be prepared to help their peers explain it. Likewise, to be respectful of the time commitments of others, the presenter must share their selected paper at least a few days before the meeting, and preferably the week before to give everyone a chance to read it thoroughly.
+[Sign up here](https://docs.google.com/spreadsheets/d/14919WwHIiKFFBcYZgF9wxACIYqh-gW-2QeDyM4WU28E/edit#gid=943003305)
 
+**Journal clubs** <br>
+
+-   Journal club serves as opportunities to present interesting new research papers from other groups. For journal clubs, all members of the lab must read the selected paper ahead of time and be prepared to help their peers explain it. Likewise, to be respectful of the time commitments of others, the presenter must share their selected paper at least a few days before the meeting, and preferably the week before to give everyone a chance to read it thoroughly.
+
+```{=html}
+<!-- -->
+```
 -   The format of journal club is largely up to the presenter, but it should walk briefly through the background to the problem, the question or need the paper addresses, how they did the work, what the results were, and how it ties back to the larger problems in the field and future directions. While the presenter can take the lead and walk the group through everything, journal clubs are a lot more engaging and educational with participation, so having the audience explain figures and interpretations is an easy way to ensure people are learning instead of just listening.
 
-**Primers** <br> - Technical primers can be great practice on teaching a topic by sharing how-to or tutorial lectures on subjects of your choosing. These are great opportunities to share a skill or approach with the group so we can all benefit from it.
+**Primers** <br>
 
+-   Technical primers can be great practice on teaching a topic by sharing how-to or tutorial lectures on subjects of your choosing. These are great opportunities to share a skill or approach with the group so we can all benefit from it.
+
+```{=html}
+<!-- -->
+```
 -   Additionally, these are spaces where we can invite an outside presenter to share with us (for example, the [Department of Biomedical Informatics' Software Engineering Team](https://cu-dbmi.github.io/set-website/about), or the [CU Office of Diversity, Equity, Inclusion & Community Engagement](https://www.cuanschutz.edu/offices/diversity-equity-inclusion-community), or a scientist with subject expertise from another lab group). It is up to the group collectively to decide which primer topics are appropriate.
 
 ### Co-work sessions
@@ -72,7 +84,9 @@ Posted by the [DBMI seminar committee](https://github.com/jananiravi/dbmi_semina
 
 \<TBD \| spontaneous\>
 
+-   Celebrations (w/ coffee/food/snacks)
 -   Random discussions/catch-up
--   Online games: https://jackbox.tv \| https://drawbattle.io
 -   Coffee/tea or ice cream for local folks
 -   Once in a while, we can dedicate the group socials to fun topics close to your heart (e.g., music, sports, books, food, ...)!
+-   Online games: https://jackbox.tv \| https://drawbattle.io (was more popular during the pandemic)
+