update notes for lecture 13

Author: kuleshov

lecture-notes/lecture13-svm-dual.ipynb

@@ -270,7 +270,7 @@
    "source": [
     "## 13.2.1. Review: Max-Margin Classification\n",
     "\n",
-    "First, let's briefly reintroduce the task of binary classification, with a linear model optimizing a max-margin objective.\n",
+    "First, let's briefly reintroduce the task of binary classification using a linear model and a max-margin objective.\n",
     "\n",
     "Consider a training dataset $\\mathcal{D} = \\{(x^{(1)}, y^{(1)}), (x^{(2)}, y^{(2)}), \\ldots, (x^{(n)}, y^{(n)})\\}$. We distinguish between two types of supervised learning problems depnding on the targets $y^{(i)}$. \n",
     "\n",