diff --git a/doc/pub/week34/html/._week34-bs009.html b/doc/pub/week34/html/._week34-bs009.html
index e078d37db..0d2306fde 100644
--- a/doc/pub/week34/html/._week34-bs009.html
+++ b/doc/pub/week34/html/._week34-bs009.html
@@ -362,7 +362,7 @@ MathJax.Hub.Config({
 <ul>
 <li> <a href="https://www.deeplearningbook.org/" target="_self">Goodfellow, Bengio, and Courville (GBC), Deep Learning</a></li>
 <li> Christopher M. Bishop (CB), Pattern Recognition and Machine Learning</li>
-<li> "Hastie, Tibshirani, and Friedman (HTF), The Elements of Statistical Learning, Springer, <a href="https://www.springer.com/gp/book/9780387848570" target="_self"><tt>https://www.springer.com/gp/book/9780387848570</tt></a>.</li>
+<li> <a href="https://www.springer.com/gp/book/9780387848570" target="_self">Hastie, Tibshirani, and Friedman (HTF), The Elements of Statistical Learning, Springer</a>.</li>
 <li> <a href="https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/" target="_self">Aurelien Geron (AG), Hands&#8209;On Machine Learning with Scikit&#8209;Learn and TensorFlow, O'Reilly</a>. This text is very useful since it contains many code examples and hands-on applications of all algorithms discussed in this course.</li>
 <li> <a href="https://probml.github.io/pml-book/book1.html" target="_self">Kevin Murphy (KM), Probabilistic Machine Learning, an Introduction</a></li>
 </ul>
diff --git a/doc/pub/week34/html/week34-reveal.html b/doc/pub/week34/html/week34-reveal.html
index 37131beae..432de430e 100644
--- a/doc/pub/week34/html/week34-reveal.html
+++ b/doc/pub/week34/html/week34-reveal.html
@@ -347,7 +347,7 @@ MathJax.Hub.Config({
 <ul>
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-<p><li> "Hastie, Tibshirani, and Friedman (HTF), The Elements of Statistical Learning, Springer, <a href="https://www.springer.com/gp/book/9780387848570" target="_blank"><tt>https://www.springer.com/gp/book/9780387848570</tt></a>.</li>
+<p><li> <a href="https://www.springer.com/gp/book/9780387848570" target="_blank">Hastie, Tibshirani, and Friedman (HTF), The Elements of Statistical Learning, Springer</a>.</li>
 <p><li> <a href="https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/" target="_blank">Aurelien Geron (AG), Hands&#8209;On Machine Learning with Scikit&#8209;Learn and TensorFlow, O'Reilly</a>. This text is very useful since it contains many code examples and hands-on applications of all algorithms discussed in this course.</li>
 <p><li> <a href="https://probml.github.io/pml-book/book1.html" target="_blank">Kevin Murphy (KM), Probabilistic Machine Learning, an Introduction</a></li>
 </ul>
diff --git a/doc/pub/week34/html/week34-solarized.html b/doc/pub/week34/html/week34-solarized.html
index e08c54e1d..3065c7ff9 100644
--- a/doc/pub/week34/html/week34-solarized.html
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@@ -425,7 +425,7 @@ MathJax.Hub.Config({
 <ul>
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 <li> Christopher M. Bishop (CB), Pattern Recognition and Machine Learning</li>
-<li> "Hastie, Tibshirani, and Friedman (HTF), The Elements of Statistical Learning, Springer, <a href="https://www.springer.com/gp/book/9780387848570" target="_blank"><tt>https://www.springer.com/gp/book/9780387848570</tt></a>.</li>
+<li> <a href="https://www.springer.com/gp/book/9780387848570" target="_blank">Hastie, Tibshirani, and Friedman (HTF), The Elements of Statistical Learning, Springer</a>.</li>
 <li> <a href="https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/" target="_blank">Aurelien Geron (AG), Hands&#8209;On Machine Learning with Scikit&#8209;Learn and TensorFlow, O'Reilly</a>. This text is very useful since it contains many code examples and hands-on applications of all algorithms discussed in this course.</li>
 <li> <a href="https://probml.github.io/pml-book/book1.html" target="_blank">Kevin Murphy (KM), Probabilistic Machine Learning, an Introduction</a></li>
 </ul>
diff --git a/doc/pub/week34/html/week34.html b/doc/pub/week34/html/week34.html
index d080ab46d..732fa7742 100644
--- a/doc/pub/week34/html/week34.html
+++ b/doc/pub/week34/html/week34.html
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 <li> Christopher M. Bishop (CB), Pattern Recognition and Machine Learning</li>
-<li> "Hastie, Tibshirani, and Friedman (HTF), The Elements of Statistical Learning, Springer, <a href="https://www.springer.com/gp/book/9780387848570" target="_blank"><tt>https://www.springer.com/gp/book/9780387848570</tt></a>.</li>
+<li> <a href="https://www.springer.com/gp/book/9780387848570" target="_blank">Hastie, Tibshirani, and Friedman (HTF), The Elements of Statistical Learning, Springer</a>.</li>
 <li> <a href="https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/" target="_blank">Aurelien Geron (AG), Hands&#8209;On Machine Learning with Scikit&#8209;Learn and TensorFlow, O'Reilly</a>. This text is very useful since it contains many code examples and hands-on applications of all algorithms discussed in this course.</li>
 <li> <a href="https://probml.github.io/pml-book/book1.html" target="_blank">Kevin Murphy (KM), Probabilistic Machine Learning, an Introduction</a></li>
 </ul>
diff --git a/doc/pub/week34/ipynb/ipynb-week34-src.tar.gz b/doc/pub/week34/ipynb/ipynb-week34-src.tar.gz
index 9fc90c8c7..e49ae1048 100644
Binary files a/doc/pub/week34/ipynb/ipynb-week34-src.tar.gz and b/doc/pub/week34/ipynb/ipynb-week34-src.tar.gz differ
diff --git a/doc/pub/week34/ipynb/week34.ipynb b/doc/pub/week34/ipynb/week34.ipynb
index a3589b149..08c3b6cf4 100644
--- a/doc/pub/week34/ipynb/week34.ipynb
+++ b/doc/pub/week34/ipynb/week34.ipynb
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+    "* [Hastie, Tibshirani, and Friedman (HTF), The Elements of Statistical Learning, Springer](https://www.springer.com/gp/book/9780387848570).\n",
     "\n",
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@@ -1360,7 +1360,7 @@
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@@ -1375,7 +1375,7 @@
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@@ -1402,7 +1402,7 @@
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@@ -1426,7 +1426,7 @@
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@@ -1452,7 +1452,7 @@
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@@ -1472,7 +1472,7 @@
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@@ -1486,7 +1486,7 @@
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@@ -1499,7 +1499,7 @@
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@@ -1510,7 +1510,7 @@
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@@ -1522,7 +1522,7 @@
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@@ -1533,7 +1533,7 @@
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@@ -1551,7 +1551,7 @@
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@@ -1563,7 +1563,7 @@
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@@ -1587,7 +1587,7 @@
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@@ -1598,7 +1598,7 @@
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@@ -1627,7 +1627,7 @@
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@@ -1638,7 +1638,7 @@
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@@ -1653,7 +1653,7 @@
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@@ -1670,7 +1670,7 @@
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@@ -1701,7 +1701,7 @@
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@@ -1713,7 +1713,7 @@
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@@ -1741,7 +1741,7 @@
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@@ -1771,7 +1771,7 @@
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@@ -1788,7 +1788,7 @@
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@@ -1800,7 +1800,7 @@
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@@ -1821,7 +1821,7 @@
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@@ -1834,7 +1834,7 @@
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@@ -1865,7 +1865,7 @@
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@@ -1877,7 +1877,7 @@
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@@ -1895,7 +1895,7 @@
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@@ -1922,7 +1922,7 @@
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@@ -1944,7 +1944,7 @@
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@@ -1982,7 +1982,7 @@
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@@ -1993,7 +1993,7 @@
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@@ -2006,7 +2006,7 @@
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@@ -2027,7 +2027,7 @@
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@@ -2039,7 +2039,7 @@
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@@ -2049,7 +2049,7 @@
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@@ -2061,7 +2061,7 @@
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@@ -2073,7 +2073,7 @@
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@@ -2085,7 +2085,7 @@
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@@ -2096,7 +2096,7 @@
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@@ -2108,7 +2108,7 @@
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@@ -2130,7 +2130,7 @@
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@@ -2142,7 +2142,7 @@
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@@ -2155,7 +2155,7 @@
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@@ -2172,7 +2172,7 @@
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@@ -2184,7 +2184,7 @@
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@@ -2194,7 +2194,7 @@
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@@ -2206,7 +2206,7 @@
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@@ -2216,7 +2216,7 @@
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@@ -2228,7 +2228,7 @@
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@@ -2238,7 +2238,7 @@
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@@ -2250,7 +2250,7 @@
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@@ -2266,7 +2266,7 @@
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@@ -2278,7 +2278,7 @@
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@@ -2289,7 +2289,7 @@
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@@ -2301,7 +2301,7 @@
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@@ -2315,7 +2315,7 @@
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@@ -2327,7 +2327,7 @@
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@@ -2352,7 +2352,7 @@
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@@ -2369,7 +2369,7 @@
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@@ -2413,7 +2413,7 @@
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@@ -2424,7 +2424,7 @@
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@@ -2446,7 +2446,7 @@
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@@ -2463,7 +2463,7 @@
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@@ -2484,7 +2484,7 @@
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@@ -2498,7 +2498,7 @@
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@@ -2527,7 +2527,7 @@
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@@ -2547,7 +2547,7 @@
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@@ -2564,7 +2564,7 @@
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@@ -2576,7 +2576,7 @@
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@@ -2594,7 +2594,7 @@
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@@ -2605,7 +2605,7 @@
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@@ -2618,7 +2618,7 @@
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@@ -2630,7 +2630,7 @@
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@@ -2661,7 +2661,7 @@
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@@ -2675,7 +2675,7 @@
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@@ -2715,7 +2715,7 @@
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@@ -2735,7 +2735,7 @@
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@@ -2767,7 +2767,7 @@
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@@ -2789,7 +2789,7 @@
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@@ -2817,7 +2817,7 @@
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@@ -2832,7 +2832,7 @@
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@@ -2844,7 +2844,7 @@
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@@ -2859,7 +2859,7 @@
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@@ -2872,7 +2872,7 @@
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@@ -2884,7 +2884,7 @@
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@@ -2894,7 +2894,7 @@
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@@ -2905,7 +2905,7 @@
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@@ -2923,7 +2923,7 @@
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@@ -2934,7 +2934,7 @@
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@@ -2946,7 +2946,7 @@
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@@ -2956,7 +2956,7 @@
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@@ -2968,7 +2968,7 @@
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@@ -2978,7 +2978,7 @@
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@@ -2990,7 +2990,7 @@
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@@ -3000,7 +3000,7 @@
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@@ -3019,7 +3019,7 @@
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@@ -3029,7 +3029,7 @@
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@@ -3041,7 +3041,7 @@
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@@ -3051,7 +3051,7 @@
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@@ -3067,7 +3067,7 @@
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@@ -3087,7 +3087,7 @@
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@@ -3097,7 +3097,7 @@
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@@ -3108,7 +3108,7 @@
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@@ -3127,7 +3127,7 @@
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@@ -3137,7 +3137,7 @@
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@@ -3149,7 +3149,7 @@
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@@ -3159,7 +3159,7 @@
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@@ -3170,7 +3170,7 @@
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@@ -3190,7 +3190,7 @@
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@@ -3202,7 +3202,7 @@
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@@ -3217,7 +3217,7 @@
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@@ -3297,7 +3297,7 @@
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@@ -3307,7 +3307,7 @@
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@@ -3319,7 +3319,7 @@
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@@ -3329,7 +3329,7 @@
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@@ -3340,7 +3340,7 @@
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@@ -3352,7 +3352,7 @@
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@@ -3362,7 +3362,7 @@
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@@ -3374,7 +3374,7 @@
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@@ -3384,7 +3384,7 @@
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@@ -3396,7 +3396,7 @@
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@@ -3409,7 +3409,7 @@
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@@ -3421,7 +3421,7 @@
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@@ -3431,7 +3431,7 @@
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@@ -3443,7 +3443,7 @@
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@@ -3455,7 +3455,7 @@
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@@ -3466,7 +3466,7 @@
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@@ -3478,7 +3478,7 @@
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@@ -3497,7 +3497,7 @@
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@@ -3510,7 +3510,7 @@
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@@ -3520,7 +3520,7 @@
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@@ -3532,7 +3532,7 @@
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@@ -3542,7 +3542,7 @@
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@@ -3554,7 +3554,7 @@
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@@ -3564,7 +3564,7 @@
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@@ -3576,7 +3576,7 @@
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@@ -3587,7 +3587,7 @@
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@@ -3599,7 +3599,7 @@
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@@ -3609,7 +3609,7 @@
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@@ -3621,7 +3621,7 @@
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@@ -3631,7 +3631,7 @@
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@@ -3643,7 +3643,7 @@
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@@ -3664,7 +3664,7 @@
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@@ -3678,7 +3678,7 @@
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@@ -3689,7 +3689,7 @@
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@@ -3701,7 +3701,7 @@
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@@ -3711,7 +3711,7 @@
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@@ -3723,7 +3723,7 @@
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@@ -3733,7 +3733,7 @@
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@@ -3745,7 +3745,7 @@
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@@ -3757,7 +3757,7 @@
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@@ -3771,7 +3771,7 @@
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@@ -3786,7 +3786,7 @@
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@@ -3797,7 +3797,7 @@
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@@ -3810,7 +3810,7 @@
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@@ -3821,7 +3821,7 @@
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@@ -3844,7 +3844,7 @@
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@@ -3858,7 +3858,7 @@
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@@ -3871,7 +3871,7 @@
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@@ -3882,7 +3882,7 @@
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@@ -3894,7 +3894,7 @@
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@@ -3905,7 +3905,7 @@
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@@ -3921,7 +3921,7 @@
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@@ -3932,7 +3932,7 @@
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@@ -3946,7 +3946,7 @@
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@@ -3968,7 +3968,7 @@
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@@ -3980,7 +3980,7 @@
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@@ -3990,7 +3990,7 @@
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@@ -4002,7 +4002,7 @@
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@@ -4014,7 +4014,7 @@
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@@ -4024,7 +4024,7 @@
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@@ -4036,7 +4036,7 @@
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@@ -4046,7 +4046,7 @@
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@@ -4058,7 +4058,7 @@
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@@ -4068,7 +4068,7 @@
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@@ -4080,7 +4080,7 @@
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@@ -4092,7 +4092,7 @@
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@@ -4102,7 +4102,7 @@
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@@ -4114,7 +4114,7 @@
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@@ -4124,7 +4124,7 @@
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@@ -4136,7 +4136,7 @@
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@@ -4148,7 +4148,7 @@
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@@ -4160,7 +4160,7 @@
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@@ -4170,7 +4170,7 @@
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@@ -4182,7 +4182,7 @@
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@@ -4192,7 +4192,7 @@
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@@ -4204,7 +4204,7 @@
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@@ -4214,7 +4214,7 @@
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@@ -4226,7 +4226,7 @@
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@@ -4237,7 +4237,7 @@
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@@ -4249,7 +4249,7 @@
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@@ -4259,7 +4259,7 @@
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@@ -4271,7 +4271,7 @@
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@@ -4281,7 +4281,7 @@
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@@ -4293,7 +4293,7 @@
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@@ -4306,7 +4306,7 @@
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@@ -4318,7 +4318,7 @@
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   {
    "cell_type": "markdown",
-   "id": "38f7416a",
+   "id": "ab7d1d9f",
    "metadata": {
     "editable": true
    },
@@ -4330,7 +4330,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fab34931",
+   "id": "5ec0e91c",
    "metadata": {
     "editable": true
    },
@@ -4342,7 +4342,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "44eadb46",
+   "id": "3561e85f",
    "metadata": {
     "editable": true
    },
@@ -4354,7 +4354,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "13a1df80",
+   "id": "530f5ed2",
    "metadata": {
     "editable": true
    },
@@ -4366,7 +4366,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cee0832e",
+   "id": "fd124b60",
    "metadata": {
     "editable": true
    },
@@ -4376,7 +4376,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a5f28ca4",
+   "id": "5991975b",
    "metadata": {
     "editable": true
    },
@@ -4388,7 +4388,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c9c5c8f2",
+   "id": "fc515197",
    "metadata": {
     "editable": true
    },
@@ -4400,7 +4400,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8acf1764",
+   "id": "af7d907e",
    "metadata": {
     "editable": true
    },
@@ -4413,7 +4413,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0c0f6b1d",
+   "id": "758750c0",
    "metadata": {
     "editable": true
    },
@@ -4440,7 +4440,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cc01bc44",
+   "id": "3640a768",
    "metadata": {
     "editable": true
    },
@@ -4451,7 +4451,7 @@
   {
    "cell_type": "code",
    "execution_count": 44,
-   "id": "546f877c",
+   "id": "4844dfef",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4547,7 +4547,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ad65bd6a",
+   "id": "c28510d4",
    "metadata": {
     "editable": true
    },
@@ -4562,7 +4562,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "01cbc753",
+   "id": "0c7206b0",
    "metadata": {
     "editable": true
    },
@@ -4584,7 +4584,7 @@
   {
    "cell_type": "code",
    "execution_count": 45,
-   "id": "f7c23b2a",
+   "id": "771dfeff",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4659,7 +4659,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b0bdb6dc",
+   "id": "2f58d309",
    "metadata": {
     "editable": true
    },
@@ -4671,7 +4671,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5f16aa82",
+   "id": "a972f2ad",
    "metadata": {
     "editable": true
    },
@@ -4740,7 +4740,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b1c16d9c",
+   "id": "d0989656",
    "metadata": {
     "editable": true
    },
@@ -4754,7 +4754,7 @@
   {
    "cell_type": "code",
    "execution_count": 46,
-   "id": "be31de5b",
+   "id": "ac7f2e24",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4767,7 +4767,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "08fc1fec",
+   "id": "e36b77b4",
    "metadata": {
     "editable": true
    },
@@ -4781,7 +4781,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "629d1a0d",
+   "id": "4695e229",
    "metadata": {
     "editable": true
    },
@@ -4794,7 +4794,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "da27be39",
+   "id": "10f56411",
    "metadata": {
     "editable": true
    },
@@ -4805,7 +4805,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "37f01a24",
+   "id": "4d18c74a",
    "metadata": {
     "editable": true
    },
@@ -4817,7 +4817,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5bb4679c",
+   "id": "814d16a8",
    "metadata": {
     "editable": true
    },
@@ -4827,7 +4827,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "288bcc47",
+   "id": "ce359a13",
    "metadata": {
     "editable": true
    },
@@ -4839,7 +4839,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "18cebb44",
+   "id": "bc10a09b",
    "metadata": {
     "editable": true
    },
@@ -4850,7 +4850,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4d229423",
+   "id": "3c1c6bac",
    "metadata": {
     "editable": true
    },
@@ -4869,7 +4869,7 @@
   {
    "cell_type": "code",
    "execution_count": 47,
-   "id": "a68c7c73",
+   "id": "14f8c148",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4885,7 +4885,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d7b8a50d",
+   "id": "f1bb42fa",
    "metadata": {
     "editable": true
    },
@@ -4895,7 +4895,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7d1dad05",
+   "id": "1b21aefb",
    "metadata": {
     "editable": true
    },
@@ -4906,7 +4906,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "995f4820",
+   "id": "c8f50072",
    "metadata": {
     "editable": true
    },
@@ -4917,7 +4917,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "192a2067",
+   "id": "117b06ed",
    "metadata": {
     "editable": true
    },
diff --git a/doc/src/week34/beamerweek34.do.txt b/doc/src/week34/beamerweek34.do.txt
index 481849bb9..bbc3ba781 100644
--- a/doc/src/week34/beamerweek34.do.txt
+++ b/doc/src/week34/beamerweek34.do.txt
@@ -118,7 +118,8 @@ In addition to the lecture notes, we recommend the books of Bishop, Hastie et al
 !bblock
 * "Goodfellow, Bengio, and Courville (GBC), Deep Learning":"https://www.deeplearningbook.org/"
 * Christopher M. Bishop (CB), Pattern Recognition and Machine Learning
-* Hastie, Tibshirani, and Friedman (HTF), The Elements of Statistical Learning, Springer, URL:"https://www.springer.com/gp/book/9780387848570".* Aurelien Geron (AG), Hands‑On Machine Learning with Scikit‑Learn and TensorFlow, O'Reilly, https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/. This text is very useful since it contains many code examples and hands-on applications of all algorithms discussed in this course.
+* "Hastie, Tibshirani, and Friedman (HTF), The Elements of Statistical Learning, Springer":"https://www.springer.com/gp/book/9780387848570".
+* "Aurelien Geron (AG), Hands‑On Machine Learning with Scikit‑Learn and TensorFlow, O'Reilly":"https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/". This text is very useful since it contains many code examples and hands-on applications of all algorithms discussed in this course.
 * "Kevin Murphy (KM), Probabilistic Machine Learning, an Introduction":"https://probml.github.io/pml-book/book1.html"
 !eblock
 
diff --git a/doc/src/week34/week34.do.txt b/doc/src/week34/week34.do.txt
index a75d49cc6..1ce5a43f1 100644
--- a/doc/src/week34/week34.do.txt
+++ b/doc/src/week34/week34.do.txt
@@ -116,7 +116,7 @@ In addition to the lecture notes, we recommend the books of Bishop, Hastie et al
 !bblock
 * "Goodfellow, Bengio, and Courville (GBC), Deep Learning":"https://www.deeplearningbook.org/"
 * Christopher M. Bishop (CB), Pattern Recognition and Machine Learning
-* "Hastie, Tibshirani, and Friedman (HTF), The Elements of Statistical Learning, Springer, URL:"https://www.springer.com/gp/book/9780387848570".
+* "Hastie, Tibshirani, and Friedman (HTF), The Elements of Statistical Learning, Springer":"https://www.springer.com/gp/book/9780387848570".
 * "Aurelien Geron (AG), Hands‑On Machine Learning with Scikit‑Learn and TensorFlow, O'Reilly":"https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/". This text is very useful since it contains many code examples and hands-on applications of all algorithms discussed in this course.
 * "Kevin Murphy (KM), Probabilistic Machine Learning, an Introduction":"https://probml.github.io/pml-book/book1.html"
 !eblock