lawrennd · Oct 27, 2026 · Oct 27, 2026 · Oct 27, 2026
diff --git a/_lectures/01-what-is-machine-learning.html b/_lectures/01-what-is-machine-learning.html
diff --git a/_lectures/02-ml-systems.html b/_lectures/02-ml-systems.html
diff --git a/_lectures/03-bayesian-methods-abuja.html b/_lectures/03-bayesian-methods-abuja.html
diff --git a/_lectures/03-probabilistic-machine-learning.html b/_lectures/03-probabilistic-machine-learning.html
diff --git a/_lectures/04-gaussian-processes.html b/_lectures/04-gaussian-processes.html
diff --git a/_notebooks/01-what-is-machine-learning.ipynb b/_notebooks/01-what-is-machine-learning.ipynb
diff --git a/_notebooks/02-ml-systems.ipynb b/_notebooks/02-ml-systems.ipynb
diff --git a/_notebooks/03-bayesian-methods-abuja.ipynb b/_notebooks/03-bayesian-methods-abuja.ipynb
diff --git a/_notebooks/03-probabilistic-machine-learning.ipynb b/_notebooks/03-probabilistic-machine-learning.ipynb
diff --git a/_notebooks/04-gaussian-processes.ipynb b/_notebooks/04-gaussian-processes.ipynb
diff --git a/slides/01-what-is-machine-learning.slides.html b/slides/01-what-is-machine-learning.slides.html
@@ -1585,10 +1585,9 @@ <h2>Objective Gradient</h2>
 <section id="objective-gradient-1" class="slide level2">
 <h2>Objective Gradient</h2>
 <p>Multiplying everything out leads to <span class="math display">\[
-\begin{aligned}
-\frac{\text{d}E(\mathbf{ w})}{\text{d}\mathbf{ w}} = &amp; -\sum_{i=1}^n
-y_i- h\left(\mathbf{ w}^\top \boldsymbol{ \phi}(\mathbf{ x})\boldsymbol{
-\phi}(\mathbf{ x}_i).
+\frac{\text{d}E(\mathbf{ w})}{\text{d}\mathbf{ w}} =
+-\sum_{i=1}^n\left(y_i - h\left(\mathbf{ w}^\top \boldsymbol{
+\phi}(\mathbf{ x}_i)\right)\right)\boldsymbol{ \phi}(\mathbf{ x}_i).
 \]</span></p>
 </section>
 <section id="optimisation-of-the-function" class="slide level2">

diff --git a/slides/03-bayesian-methods-abuja.slides.html b/slides/03-bayesian-methods-abuja.slides.html
@@ -977,8 +977,7 @@ <h2>Reminder on the Term “Bayesian”</h2>
 stochastic variables.</li>
 <li>Proposed by <span class="citation"
 data-cites="Laplace:memoire74">Laplace (1774)</span> and <span
-class="citation"
-data-cites="Bayes:doctrine63">(<strong>Bayes:doctrine63?</strong>)</span>
+class="citation" data-cites="Bayes-doctrine63">Bayes (1763)</span>
 independently.</li>
 <li>For early statisticians this was very controversial (Fisher et
 al).</li>
@@ -1574,6 +1573,11 @@ <h2 class="scrollable">Thanks!</h2>
 </ul>
 <div id="refs" class="references csl-bib-body hanging-indent"
 role="list">
+<div id="ref-Bayes-doctrine63" class="csl-entry" role="listitem">
+Bayes, T., 1763. An essay towards solving a problem in the doctrine of
+chances. Philosophical Transactions of the Royal Society 53, 370–418. <a
+href="https://doi.org/10.1098/rstl.1763.0053">https://doi.org/10.1098/rstl.1763.0053</a>
+</div>
 <div id="ref-Bishop:book06" class="csl-entry" role="listitem">
 Bishop, C.M., 2006. Pattern recognition and machine learning. springer.
 </div>

diff --git a/slides/03-probabilistic-machine-learning.slides.html b/slides/03-probabilistic-machine-learning.slides.html
@@ -977,8 +977,7 @@ <h2>Reminder on the Term “Bayesian”</h2>
 stochastic variables.</li>
 <li>Proposed by <span class="citation"
 data-cites="Laplace:memoire74">Laplace (1774)</span> and <span
-class="citation"
-data-cites="Bayes:doctrine63">(<strong>Bayes:doctrine63?</strong>)</span>
+class="citation" data-cites="Bayes-doctrine63">Bayes (1763)</span>
 independently.</li>
 <li>For early statisticians this was very controversial (Fisher et
 al).</li>
@@ -1547,6 +1546,11 @@ <h3 id="other-reading">Other Reading</h3>
 <h3 class="unnumbered" id="references">References</h3>
 <div id="refs" class="references csl-bib-body hanging-indent"
 role="list">
+<div id="ref-Bayes-doctrine63" class="csl-entry" role="listitem">
+Bayes, T., 1763. An essay towards solving a problem in the doctrine of
+chances. Philosophical Transactions of the Royal Society 53, 370–418. <a
+href="https://doi.org/10.1098/rstl.1763.0053">https://doi.org/10.1098/rstl.1763.0053</a>
+</div>
 <div id="ref-Bishop:book06" class="csl-entry" role="listitem">
 Bishop, C.M., 2006. Pattern recognition and machine learning. springer.
 </div>