Deploying to gh-pages from @ 6904d5c 🚀

fe.html

@@ -192,6 +192,7 @@ <h2 id="html--css--js"><a class="header" href="#html--css--js">HTML &amp; CSS &a
 <li><a href="https://anthonyhobday.com/sideprojects/saferules/">Visual design rules you can safely follow every time</a></li>
 <li><a href="https://fffuel.co/css-selectors/">CSS Selectors: A Visual Guide</a></li>
 <li><a href="https://caniuse.com/">Can I use?</a></li>
+<li><a href="https://svg-tutorial.com/">SVG Tutorial</a></li>
 </ul>
 
                     </main>

from-scratch.html

@@ -227,6 +227,7 @@ <h2 id="from-scratch"><a class="header" href="#from-scratch">From Scratch</a></h
 <li><a href="https://rayanfam.com/topics/hypervisor-from-scratch-part-1/">Hypervisor From Scratch</a></li>
 <li><a href="https://www.timdbg.com/posts/writing-a-debugger-from-scratch-part-1/">Writing a Debugger From Scratch</a></li>
 <li><a href="http://c9x.me/articles/gthreads/intro.html">Green Threads Explained</a></li>
+<li><a href="https://nolanlawson.com/2023/12/02/lets-learn-how-modern-javascript-frameworks-work-by-building-one/">Let’s learn how modern JavaScript frameworks work by building one</a></li>
 </ul>
 <p>Other lists:</p>
 <ul>

mldl.html

@@ -190,7 +190,7 @@ <h2 id="machine-learning-and-deep-learning"><a class="header" href="#machine-lea
 <li><a href="https://d2l.ai/">Dive into Deep Learning</a></li>
 <li>Manning &amp; Schutze, Foundations of Statistical Natural Language Processing</li>
 <li>Jurafsky &amp; Martin, <a href="https://web.stanford.edu/~jurafsky/slp3/">Speech and Language Processing</a></li>
-<li>Eisenstein, [Introduction to Natural Language Processing]</li>
+<li>Eisenstein, <a href="https://github.com/jacobeisenstein/gt-nlp-class/blob/master/notes/eisenstein-nlp-notes.pdf">Introduction to Natural Language Processing</a></li>
 <li>Molnar, <a href="https://christophm.github.io/interpretable-ml-book/">Interpretable Machine Learning</a></li>
 <li>McKay, <a href="http://www.inference.org.uk/mackay/itprnn/book.html">Information Theory, Inference and Learning Algorithms</a></li>
 <li>Hastie, Tibshirani &amp; Friedman, The Elements of Statistical Learning</li>
@@ -201,6 +201,7 @@ <h2 id="machine-learning-and-deep-learning"><a class="header" href="#machine-lea
 <li><a href="https://www.ruder.io/tag/natural-language-processing/">ruder.io</a></li>
 <li><a href="https://github.com/mihail911/nlp-library">nlp-library</a></li>
 <li><a href="https://aegeorge42.github.io/">Neural networks from scratch</a></li>
+<li><a href="https://bbycroft.net/llm">LLM Visualization</a></li>
 </ul>
 
                     </main>

print.html

@@ -961,6 +961,7 @@ <h2 id="other-programming-languages-1"><a class="header" href="#other-programmin
 <li><a href="https://anthonyhobday.com/sideprojects/saferules/">Visual design rules you can safely follow every time</a></li>
 <li><a href="https://fffuel.co/css-selectors/">CSS Selectors: A Visual Guide</a></li>
 <li><a href="https://caniuse.com/">Can I use?</a></li>
+<li><a href="https://svg-tutorial.com/">SVG Tutorial</a></li>
 </ul>
 <div style="break-before: page; page-break-before: always;"></div><h2 id="unixlinux"><a class="header" href="#unixlinux">UNIX/Linux</a></h2>
 <ul>
@@ -1070,6 +1071,7 @@ <h2 id="other-programming-languages-1"><a class="header" href="#other-programmin
 <li><a href="https://rayanfam.com/topics/hypervisor-from-scratch-part-1/">Hypervisor From Scratch</a></li>
 <li><a href="https://www.timdbg.com/posts/writing-a-debugger-from-scratch-part-1/">Writing a Debugger From Scratch</a></li>
 <li><a href="http://c9x.me/articles/gthreads/intro.html">Green Threads Explained</a></li>
+<li><a href="https://nolanlawson.com/2023/12/02/lets-learn-how-modern-javascript-frameworks-work-by-building-one/">Let’s learn how modern JavaScript frameworks work by building one</a></li>
 </ul>
 <p>Other lists:</p>
 <ul>
@@ -1175,7 +1177,7 @@ <h2 id="other-programming-languages-1"><a class="header" href="#other-programmin
 <li><a href="https://d2l.ai/">Dive into Deep Learning</a></li>
 <li>Manning &amp; Schutze, Foundations of Statistical Natural Language Processing</li>
 <li>Jurafsky &amp; Martin, <a href="https://web.stanford.edu/~jurafsky/slp3/">Speech and Language Processing</a></li>
-<li>Eisenstein, [Introduction to Natural Language Processing]</li>
+<li>Eisenstein, <a href="https://github.com/jacobeisenstein/gt-nlp-class/blob/master/notes/eisenstein-nlp-notes.pdf">Introduction to Natural Language Processing</a></li>
 <li>Molnar, <a href="https://christophm.github.io/interpretable-ml-book/">Interpretable Machine Learning</a></li>
 <li>McKay, <a href="http://www.inference.org.uk/mackay/itprnn/book.html">Information Theory, Inference and Learning Algorithms</a></li>
 <li>Hastie, Tibshirani &amp; Friedman, The Elements of Statistical Learning</li>
@@ -1186,6 +1188,7 @@ <h2 id="other-programming-languages-1"><a class="header" href="#other-programmin
 <li><a href="https://www.ruder.io/tag/natural-language-processing/">ruder.io</a></li>
 <li><a href="https://github.com/mihail911/nlp-library">nlp-library</a></li>
 <li><a href="https://aegeorge42.github.io/">Neural networks from scratch</a></li>
+<li><a href="https://bbycroft.net/llm">LLM Visualization</a></li>
 </ul>
 <div style="break-before: page; page-break-before: always;"></div><h2 id="best-practices-common-pitfalls-curious-stuff--basic-things-you-should-know"><a class="header" href="#best-practices-common-pitfalls-curious-stuff--basic-things-you-should-know">Best Practices, Common Pitfalls, Curious Stuff &amp; Basic Things You Should Know</a></h2>
 <ul>