diff --git a/doc/pub/week38/html/._week38-bs014.html b/doc/pub/week38/html/._week38-bs014.html
index 28b47f286..8290e2bb1 100644
--- a/doc/pub/week38/html/._week38-bs014.html
+++ b/doc/pub/week38/html/._week38-bs014.html
@@ -467,10 +467,10 @@ clf <span style="color: #666666">=</span> LinearRegression(fit_intercept<span st
 <span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;Sklearn fitted beta: </span><span style="color: #BB6688; font-weight: bold">{</span>clf<span style="color: #666666">.</span>coef_<span style="color: #BB6688; font-weight: bold">}</span><span style="color: #BA2121">&quot;</span>)
 ypredictOwn <span style="color: #666666">=</span> X <span style="color: #666666">@</span> beta
 ypredictSKL <span style="color: #666666">=</span> skl<span style="color: #666666">.</span>predict(X)
-<span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;MSE with intercept column: </span><span style="color: #BB6688; font-weight: bold">{</span>intercept<span style="color: #BB6688; font-weight: bold">}</span><span style="color: #BA2121">&quot;</span>)
-<span style="color: #008000">print</span>(MSE(y,ypredictOwn)
-<span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;MSE with intercept column from SKL: </span><span style="color: #BB6688; font-weight: bold">{</span>intercept<span style="color: #BB6688; font-weight: bold">}</span><span style="color: #BA2121">&quot;</span>)
-<span style="color: #008000">print</span>(MSE(y,ypredictSKL)
+<span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;MSE with intercept column&quot;</span>)
+<span style="color: #008000">print</span>(MSE(y,ypredictOwn))
+<span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;MSE with intercept column from SKL&quot;</span>)
+<span style="color: #008000">print</span>(MSE(y,ypredictSKL))
 
 
 plt<span style="color: #666666">.</span>figure()
@@ -501,10 +501,10 @@ intercept <span style="color: #666666">=</span> np<span style="color: #666666">.
 <span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;Sklearn fitted beta (without intercept): </span><span style="color: #BB6688; font-weight: bold">{</span>clf<span style="color: #666666">.</span>coef_<span style="color: #BB6688; font-weight: bold">}</span><span style="color: #BA2121">&quot;</span>)
 ypredictOwn <span style="color: #666666">=</span> X <span style="color: #666666">@</span> beta
 ypredictSKL <span style="color: #666666">=</span> skl<span style="color: #666666">.</span>predict(X)
-<span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;MSE with Manual intercept: </span><span style="color: #BB6688; font-weight: bold">{</span>intercept<span style="color: #BB6688; font-weight: bold">}</span><span style="color: #BA2121">&quot;</span>)
-<span style="color: #008000">print</span>(MSE(y,ypredictOwn)
-<span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;MSE with Sklearn intercept: </span><span style="color: #BB6688; font-weight: bold">{</span>clf<span style="color: #666666">.</span>intercept_<span style="color: #BB6688; font-weight: bold">}</span><span style="color: #BA2121">&quot;</span>)
-<span style="color: #008000">print</span>(MSE(y,ypredictSKL)
+<span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;MSE with Manual intercept&quot;</span>)
+<span style="color: #008000">print</span>(MSE(y,ypredictOwn))
+<span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;MSE with Sklearn intercept&quot;</span>)
+<span style="color: #008000">print</span>(MSE(y,ypredictSKL))
 
 plt<span style="color: #666666">.</span>plot(x, X <span style="color: #666666">@</span> beta <span style="color: #666666">+</span> intercept, <span style="color: #BA2121">&quot;--&quot;</span>, label<span style="color: #666666">=</span><span style="color: #BA2121">&quot;Fit (manual intercept)&quot;</span>)
 plt<span style="color: #666666">.</span>plot(x, clf<span style="color: #666666">.</span>predict(X), <span style="color: #BA2121">&quot;--&quot;</span>, label<span style="color: #666666">=</span><span style="color: #BA2121">&quot;Sklearn (fit_intercept=True)&quot;</span>)
diff --git a/doc/pub/week38/html/week38-reveal.html b/doc/pub/week38/html/week38-reveal.html
index 604d56d16..22973f249 100644
--- a/doc/pub/week38/html/week38-reveal.html
+++ b/doc/pub/week38/html/week38-reveal.html
@@ -720,10 +720,10 @@ clf = LinearRegression(fit_intercept=<span style="color: #8B008B; font-weight: b
 <span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;Sklearn fitted beta: {</span>clf.coef_<span style="color: #CD5555">}&quot;</span>)
 ypredictOwn = X @ beta
 ypredictSKL = skl.predict(X)
-<span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;MSE with intercept column: {</span>intercept<span style="color: #CD5555">}&quot;</span>)
-<span style="color: #658b00">print</span>(MSE(y,ypredictOwn)
-<span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;MSE with intercept column from SKL: {</span>intercept<span style="color: #CD5555">}&quot;</span>)
-<span style="color: #658b00">print</span>(MSE(y,ypredictSKL)
+<span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;MSE with intercept column&quot;</span>)
+<span style="color: #658b00">print</span>(MSE(y,ypredictOwn))
+<span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;MSE with intercept column from SKL&quot;</span>)
+<span style="color: #658b00">print</span>(MSE(y,ypredictSKL))
 
 
 plt.figure()
@@ -754,10 +754,10 @@ intercept = np.mean(y_offset - X_offset @ beta)
 <span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;Sklearn fitted beta (without intercept): {</span>clf.coef_<span style="color: #CD5555">}&quot;</span>)
 ypredictOwn = X @ beta
 ypredictSKL = skl.predict(X)
-<span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;MSE with Manual intercept: {</span>intercept<span style="color: #CD5555">}&quot;</span>)
-<span style="color: #658b00">print</span>(MSE(y,ypredictOwn)
-<span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;MSE with Sklearn intercept: {</span>clf.intercept_<span style="color: #CD5555">}&quot;</span>)
-<span style="color: #658b00">print</span>(MSE(y,ypredictSKL)
+<span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;MSE with Manual intercept&quot;</span>)
+<span style="color: #658b00">print</span>(MSE(y,ypredictOwn))
+<span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;MSE with Sklearn intercept&quot;</span>)
+<span style="color: #658b00">print</span>(MSE(y,ypredictSKL))
 
 plt.plot(x, X @ beta + intercept, <span style="color: #CD5555">&quot;--&quot;</span>, label=<span style="color: #CD5555">&quot;Fit (manual intercept)&quot;</span>)
 plt.plot(x, clf.predict(X), <span style="color: #CD5555">&quot;--&quot;</span>, label=<span style="color: #CD5555">&quot;Sklearn (fit_intercept=True)&quot;</span>)
diff --git a/doc/pub/week38/html/week38-solarized.html b/doc/pub/week38/html/week38-solarized.html
index 375cbd323..da89caf98 100644
--- a/doc/pub/week38/html/week38-solarized.html
+++ b/doc/pub/week38/html/week38-solarized.html
@@ -854,10 +854,10 @@ clf = LinearRegression(fit_intercept=<span style="color: #8B008B; font-weight: b
 <span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;Sklearn fitted beta: {</span>clf.coef_<span style="color: #CD5555">}&quot;</span>)
 ypredictOwn = X @ beta
 ypredictSKL = skl.predict(X)
-<span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;MSE with intercept column: {</span>intercept<span style="color: #CD5555">}&quot;</span>)
-<span style="color: #658b00">print</span>(MSE(y,ypredictOwn)
-<span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;MSE with intercept column from SKL: {</span>intercept<span style="color: #CD5555">}&quot;</span>)
-<span style="color: #658b00">print</span>(MSE(y,ypredictSKL)
+<span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;MSE with intercept column&quot;</span>)
+<span style="color: #658b00">print</span>(MSE(y,ypredictOwn))
+<span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;MSE with intercept column from SKL&quot;</span>)
+<span style="color: #658b00">print</span>(MSE(y,ypredictSKL))
 
 
 plt.figure()
@@ -888,10 +888,10 @@ intercept = np.mean(y_offset - X_offset @ beta)
 <span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;Sklearn fitted beta (without intercept): {</span>clf.coef_<span style="color: #CD5555">}&quot;</span>)
 ypredictOwn = X @ beta
 ypredictSKL = skl.predict(X)
-<span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;MSE with Manual intercept: {</span>intercept<span style="color: #CD5555">}&quot;</span>)
-<span style="color: #658b00">print</span>(MSE(y,ypredictOwn)
-<span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;MSE with Sklearn intercept: {</span>clf.intercept_<span style="color: #CD5555">}&quot;</span>)
-<span style="color: #658b00">print</span>(MSE(y,ypredictSKL)
+<span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;MSE with Manual intercept&quot;</span>)
+<span style="color: #658b00">print</span>(MSE(y,ypredictOwn))
+<span style="color: #658b00">print</span>(<span style="color: #CD5555">f&quot;MSE with Sklearn intercept&quot;</span>)
+<span style="color: #658b00">print</span>(MSE(y,ypredictSKL))
 
 plt.plot(x, X @ beta + intercept, <span style="color: #CD5555">&quot;--&quot;</span>, label=<span style="color: #CD5555">&quot;Fit (manual intercept)&quot;</span>)
 plt.plot(x, clf.predict(X), <span style="color: #CD5555">&quot;--&quot;</span>, label=<span style="color: #CD5555">&quot;Sklearn (fit_intercept=True)&quot;</span>)
diff --git a/doc/pub/week38/html/week38.html b/doc/pub/week38/html/week38.html
index 14e83eaf7..d467ae5e5 100644
--- a/doc/pub/week38/html/week38.html
+++ b/doc/pub/week38/html/week38.html
@@ -859,10 +859,10 @@ clf <span style="color: #666666">=</span> LinearRegression(fit_intercept<span st
 <span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;Sklearn fitted beta: </span><span style="color: #BB6688; font-weight: bold">{</span>clf<span style="color: #666666">.</span>coef_<span style="color: #BB6688; font-weight: bold">}</span><span style="color: #BA2121">&quot;</span>)
 ypredictOwn <span style="color: #666666">=</span> X <span style="color: #666666">@</span> beta
 ypredictSKL <span style="color: #666666">=</span> skl<span style="color: #666666">.</span>predict(X)
-<span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;MSE with intercept column: </span><span style="color: #BB6688; font-weight: bold">{</span>intercept<span style="color: #BB6688; font-weight: bold">}</span><span style="color: #BA2121">&quot;</span>)
-<span style="color: #008000">print</span>(MSE(y,ypredictOwn)
-<span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;MSE with intercept column from SKL: </span><span style="color: #BB6688; font-weight: bold">{</span>intercept<span style="color: #BB6688; font-weight: bold">}</span><span style="color: #BA2121">&quot;</span>)
-<span style="color: #008000">print</span>(MSE(y,ypredictSKL)
+<span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;MSE with intercept column&quot;</span>)
+<span style="color: #008000">print</span>(MSE(y,ypredictOwn))
+<span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;MSE with intercept column from SKL&quot;</span>)
+<span style="color: #008000">print</span>(MSE(y,ypredictSKL))
 
 
 plt<span style="color: #666666">.</span>figure()
@@ -893,10 +893,10 @@ intercept <span style="color: #666666">=</span> np<span style="color: #666666">.
 <span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;Sklearn fitted beta (without intercept): </span><span style="color: #BB6688; font-weight: bold">{</span>clf<span style="color: #666666">.</span>coef_<span style="color: #BB6688; font-weight: bold">}</span><span style="color: #BA2121">&quot;</span>)
 ypredictOwn <span style="color: #666666">=</span> X <span style="color: #666666">@</span> beta
 ypredictSKL <span style="color: #666666">=</span> skl<span style="color: #666666">.</span>predict(X)
-<span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;MSE with Manual intercept: </span><span style="color: #BB6688; font-weight: bold">{</span>intercept<span style="color: #BB6688; font-weight: bold">}</span><span style="color: #BA2121">&quot;</span>)
-<span style="color: #008000">print</span>(MSE(y,ypredictOwn)
-<span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;MSE with Sklearn intercept: </span><span style="color: #BB6688; font-weight: bold">{</span>clf<span style="color: #666666">.</span>intercept_<span style="color: #BB6688; font-weight: bold">}</span><span style="color: #BA2121">&quot;</span>)
-<span style="color: #008000">print</span>(MSE(y,ypredictSKL)
+<span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;MSE with Manual intercept&quot;</span>)
+<span style="color: #008000">print</span>(MSE(y,ypredictOwn))
+<span style="color: #008000">print</span>(<span style="color: #BA2121">f&quot;MSE with Sklearn intercept&quot;</span>)
+<span style="color: #008000">print</span>(MSE(y,ypredictSKL))
 
 plt<span style="color: #666666">.</span>plot(x, X <span style="color: #666666">@</span> beta <span style="color: #666666">+</span> intercept, <span style="color: #BA2121">&quot;--&quot;</span>, label<span style="color: #666666">=</span><span style="color: #BA2121">&quot;Fit (manual intercept)&quot;</span>)
 plt<span style="color: #666666">.</span>plot(x, clf<span style="color: #666666">.</span>predict(X), <span style="color: #BA2121">&quot;--&quot;</span>, label<span style="color: #666666">=</span><span style="color: #BA2121">&quot;Sklearn (fit_intercept=True)&quot;</span>)
diff --git a/doc/pub/week38/ipynb/ipynb-week38-src.tar.gz b/doc/pub/week38/ipynb/ipynb-week38-src.tar.gz
index f5c873c35..1deffa1e8 100644
Binary files a/doc/pub/week38/ipynb/ipynb-week38-src.tar.gz and b/doc/pub/week38/ipynb/ipynb-week38-src.tar.gz differ
diff --git a/doc/pub/week38/ipynb/week38.ipynb b/doc/pub/week38/ipynb/week38.ipynb
index bd24bc15f..e70fc369c 100644
--- a/doc/pub/week38/ipynb/week38.ipynb
+++ b/doc/pub/week38/ipynb/week38.ipynb
@@ -783,10 +783,10 @@
     "print(f\"Sklearn fitted beta: {clf.coef_}\")\n",
     "ypredictOwn = X @ beta\n",
     "ypredictSKL = skl.predict(X)\n",
-    "print(f\"MSE with intercept column: {intercept}\")\n",
-    "print(MSE(y,ypredictOwn)\n",
-    "print(f\"MSE with intercept column from SKL: {intercept}\")\n",
-    "print(MSE(y,ypredictSKL)\n",
+    "print(f\"MSE with intercept column\")\n",
+    "print(MSE(y,ypredictOwn))\n",
+    "print(f\"MSE with intercept column from SKL\")\n",
+    "print(MSE(y,ypredictSKL))\n",
     "\n",
     "\n",
     "plt.figure()\n",
@@ -817,10 +817,10 @@
     "print(f\"Sklearn fitted beta (without intercept): {clf.coef_}\")\n",
     "ypredictOwn = X @ beta\n",
     "ypredictSKL = skl.predict(X)\n",
-    "print(f\"MSE with Manual intercept: {intercept}\")\n",
-    "print(MSE(y,ypredictOwn)\n",
-    "print(f\"MSE with Sklearn intercept: {clf.intercept_}\")\n",
-    "print(MSE(y,ypredictSKL)\n",
+    "print(f\"MSE with Manual intercept\")\n",
+    "print(MSE(y,ypredictOwn))\n",
+    "print(f\"MSE with Sklearn intercept\")\n",
+    "print(MSE(y,ypredictSKL))\n",
     "\n",
     "plt.plot(x, X @ beta + intercept, \"--\", label=\"Fit (manual intercept)\")\n",
     "plt.plot(x, clf.predict(X), \"--\", label=\"Sklearn (fit_intercept=True)\")\n",
diff --git a/doc/src/week38/week38.do.txt b/doc/src/week38/week38.do.txt
index 6bd895d5d..658aea36a 100644
--- a/doc/src/week38/week38.do.txt
+++ b/doc/src/week38/week38.do.txt
@@ -499,10 +499,10 @@ print(f"Fitted beta: {beta}")
 print(f"Sklearn fitted beta: {clf.coef_}")
 ypredictOwn = X @ beta
 ypredictSKL = skl.predict(X)
-print(f"MSE with intercept column: {intercept}")
-print(MSE(y,ypredictOwn)
-print(f"MSE with intercept column from SKL: {intercept}")
-print(MSE(y,ypredictSKL)
+print(f"MSE with intercept column")
+print(MSE(y,ypredictOwn))
+print(f"MSE with intercept column from SKL")
+print(MSE(y,ypredictSKL))
 
 
 plt.figure()
@@ -533,10 +533,10 @@ print(f"Sklearn intercept: {clf.intercept_}")
 print(f"Sklearn fitted beta (without intercept): {clf.coef_}")
 ypredictOwn = X @ beta
 ypredictSKL = skl.predict(X)
-print(f"MSE with Manual intercept: {intercept}")
-print(MSE(y,ypredictOwn)
-print(f"MSE with Sklearn intercept: {clf.intercept_}")
-print(MSE(y,ypredictSKL)
+print(f"MSE with Manual intercept")
+print(MSE(y,ypredictOwn))
+print(f"MSE with Sklearn intercept")
+print(MSE(y,ypredictSKL))
 
 plt.plot(x, X @ beta + intercept, "--", label="Fit (manual intercept)")
 plt.plot(x, clf.predict(X), "--", label="Sklearn (fit_intercept=True)")