deploy: 64122eb

appendix/02_errata/index.html

@@ -88,6 +88,8 @@ <h2 id="errata-in-the-slides-shown-in-the-videos">Errata in the slides shown in
 <li>Chapter 13.7: Slide 4/14 switched x and y in the proposition regarding zero conditional entropy</li>
 <li>Chapter 13.7: Slide 14/14 added missing 0.5 factor in the entropy of the multivariate Gaussian</li>
 <li>Chapter 13.7: Slide 14/14 added parentheses to make log less ambiguous</li>
+<li>Chapter 15.2 (Ridge Regression): Slide 4/10 clarified meaning of green dot in plot in comment</li>
+<li>Chapter 15.8 (Bayesian Priors): Slide 5/5 renew plot and add comment on ybar</li>
 <li>Chapter 17.1: Slide 6/11 Typo in f</li>
 <li>Chapter 17.3: Slide 2/6 Show how to get phi(x) explicitly, and the last component of phi(x) should be b instead of sqrt(b).</li>
 <li>Chapter 17.3: Slide 2/7 Assume gamma = 1 to avoid conflict with geometric distances</li>

appendix/index.html

@@ -173,6 +173,8 @@ <h1>Appendix</h1>
 <li>Chapter 13.7: Slide 4/14 switched x and y in the proposition regarding zero conditional entropy</li>
 <li>Chapter 13.7: Slide 14/14 added missing 0.5 factor in the entropy of the multivariate Gaussian</li>
 <li>Chapter 13.7: Slide 14/14 added parentheses to make log less ambiguous</li>
+<li>Chapter 15.2 (Ridge Regression): Slide 4/10 clarified meaning of green dot in plot in comment</li>
+<li>Chapter 15.8 (Bayesian Priors): Slide 5/5 renew plot and add comment on ybar</li>
 <li>Chapter 17.1: Slide 6/11 Typo in f</li>
 <li>Chapter 17.3: Slide 2/6 Show how to get phi(x) explicitly, and the last component of phi(x) should be b instead of sqrt(b).</li>
 <li>Chapter 17.3: Slide 2/7 Assume gamma = 1 to avoid conflict with geometric distances</li>