start in second lecture

Author: faressc

slides/02-machine_learning_fundamentals.md

@@ -2,3 +2,36 @@
 
 ---
 
+## Mathematical Foundations
+
+<div class="timeline-container" style="flex-direction: row;">
+    <div style="width: 20%;">
+        <div class="timeline-title">Calculus & Linear Algebra</div>
+        <div class="timeline-text">Basis for optimization algorithms and machine learning model operations</div>
+    </div>
+    <div class="timeline" style="width: 80%; --start-year: 1676; --end-year: 1951;" data-timeline-fragments-select="1676:0,1805:0,1847:0,1951:0">
+        {{TIMELINE:timeline_calculus_linear_algebra}}
+    </div>
+</div>
+
+<div class="timeline-container" style="flex-direction: row;">
+    <div style="width: 20%;">
+        <div class="timeline-title">Probability & Statistics</div>
+        <div class="timeline-text">Basis for Bayesian methods, statistical inference, and generative models</div>
+    </div>
+    <div class="timeline" style="width: 80%; --start-year: 1676; --end-year: 1951;" data-timeline-fragments-select="1815:0">
+        {{TIMELINE:timeline_probability_statistics}}
+    </div>
+</div>
+
+<div class="timeline-container" style="flex-direction: row;">
+    <div style="width: 20%;">
+        <div class="timeline-title">Information & Computation</div>
+        <div class="timeline-text">Foundations of algorithmic thinking and information theory</div>
+    </div>
+    <div class="timeline" style="width: 80%; --start-year: 1676; --end-year: 1951;" data-timeline-fragments-select="1843:0,1936:0,1947:0,1948:0">
+        {{TIMELINE:timeline_information_computation}}
+    </div>
+</div>
+
+---