diff --git a/doc/pub/week36/html/week36-reveal.html b/doc/pub/week36/html/week36-reveal.html
index c330b6cec..b85742573 100644
--- a/doc/pub/week36/html/week36-reveal.html
+++ b/doc/pub/week36/html/week36-reveal.html
@@ -1023,7 +1023,7 @@ lambdas = np.logspace(-<span style="color: #B452CD">4</span>, <span style="color
 <span style="color: #228B22">#    print(MSEPredict[i])</span>
     <span style="color: #228B22"># Now plot the results</span>
 plt.figure()
-plt.plot(np.log10(lambdas), MSEPredict, <span style="color: #CD5555">&#39;r--&#39;</span>, label = <span style="color: #CD5555">&#39;MSE Ridge Test&#39;</span>)
+plt.plot(np.log10(lambdas), MSEPredict, <span style="color: #CD5555">&#39;r--&#39;</span>, label = <span style="color: #CD5555">&#39;MSE Ridge Train&#39;</span>)
 plt.xlabel(<span style="color: #CD5555">&#39;log10(lambda)&#39;</span>)
 plt.ylabel(<span style="color: #CD5555">&#39;MSE&#39;</span>)
 plt.legend()
@@ -1086,7 +1086,7 @@ lambdas = np.logspace(-<span style="color: #B452CD">4</span>, <span style="color
     RegLasso = linear_model.Lasso(lmb)
     RegLasso.fit(X,y)
     ypredictLasso = RegLasso.predict(X)
-    <span style="color: #658b00">print</span>(RegLasso_coef_)
+    <span style="color: #658b00">print</span>(RegLasso.coef_)
     MSELassoPredict[i] = MSE(y,ypredictLasso)
 <span style="color: #228B22"># Now plot the results</span>
 plt.figure()
diff --git a/doc/pub/week36/html/week36-solarized.html b/doc/pub/week36/html/week36-solarized.html
index 8ea13d897..0786fd9e2 100644
--- a/doc/pub/week36/html/week36-solarized.html
+++ b/doc/pub/week36/html/week36-solarized.html
@@ -1046,7 +1046,7 @@ lambdas = np.logspace(-<span style="color: #B452CD">4</span>, <span style="color
 <span style="color: #228B22">#    print(MSEPredict[i])</span>
     <span style="color: #228B22"># Now plot the results</span>
 plt.figure()
-plt.plot(np.log10(lambdas), MSEPredict, <span style="color: #CD5555">&#39;r--&#39;</span>, label = <span style="color: #CD5555">&#39;MSE Ridge Test&#39;</span>)
+plt.plot(np.log10(lambdas), MSEPredict, <span style="color: #CD5555">&#39;r--&#39;</span>, label = <span style="color: #CD5555">&#39;MSE Ridge Train&#39;</span>)
 plt.xlabel(<span style="color: #CD5555">&#39;log10(lambda)&#39;</span>)
 plt.ylabel(<span style="color: #CD5555">&#39;MSE&#39;</span>)
 plt.legend()
@@ -1109,7 +1109,7 @@ lambdas = np.logspace(-<span style="color: #B452CD">4</span>, <span style="color
     RegLasso = linear_model.Lasso(lmb)
     RegLasso.fit(X,y)
     ypredictLasso = RegLasso.predict(X)
-    <span style="color: #658b00">print</span>(RegLasso_coef_)
+    <span style="color: #658b00">print</span>(RegLasso.coef_)
     MSELassoPredict[i] = MSE(y,ypredictLasso)
 <span style="color: #228B22"># Now plot the results</span>
 plt.figure()
diff --git a/doc/pub/week36/html/week36.html b/doc/pub/week36/html/week36.html
index 4a73d1fc6..99b7d962f 100644
--- a/doc/pub/week36/html/week36.html
+++ b/doc/pub/week36/html/week36.html
@@ -1051,7 +1051,7 @@ lambdas <span style="color: #666666">=</span> np<span style="color: #666666">.</
 <span style="color: #408080; font-style: italic">#    print(MSEPredict[i])</span>
     <span style="color: #408080; font-style: italic"># Now plot the results</span>
 plt<span style="color: #666666">.</span>figure()
-plt<span style="color: #666666">.</span>plot(np<span style="color: #666666">.</span>log10(lambdas), MSEPredict, <span style="color: #BA2121">&#39;r--&#39;</span>, label <span style="color: #666666">=</span> <span style="color: #BA2121">&#39;MSE Ridge Test&#39;</span>)
+plt<span style="color: #666666">.</span>plot(np<span style="color: #666666">.</span>log10(lambdas), MSEPredict, <span style="color: #BA2121">&#39;r--&#39;</span>, label <span style="color: #666666">=</span> <span style="color: #BA2121">&#39;MSE Ridge Train&#39;</span>)
 plt<span style="color: #666666">.</span>xlabel(<span style="color: #BA2121">&#39;log10(lambda)&#39;</span>)
 plt<span style="color: #666666">.</span>ylabel(<span style="color: #BA2121">&#39;MSE&#39;</span>)
 plt<span style="color: #666666">.</span>legend()
@@ -1114,7 +1114,7 @@ lambdas <span style="color: #666666">=</span> np<span style="color: #666666">.</
     RegLasso <span style="color: #666666">=</span> linear_model<span style="color: #666666">.</span>Lasso(lmb)
     RegLasso<span style="color: #666666">.</span>fit(X,y)
     ypredictLasso <span style="color: #666666">=</span> RegLasso<span style="color: #666666">.</span>predict(X)
-    <span style="color: #008000">print</span>(RegLasso_coef_)
+    <span style="color: #008000">print</span>(RegLasso<span style="color: #666666">.</span>coef_)
     MSELassoPredict[i] <span style="color: #666666">=</span> MSE(y,ypredictLasso)
 <span style="color: #408080; font-style: italic"># Now plot the results</span>
 plt<span style="color: #666666">.</span>figure()
diff --git a/doc/pub/week36/ipynb/ipynb-week36-src.tar.gz b/doc/pub/week36/ipynb/ipynb-week36-src.tar.gz
index 3c840b2d5..8217dc872 100644
Binary files a/doc/pub/week36/ipynb/ipynb-week36-src.tar.gz and b/doc/pub/week36/ipynb/ipynb-week36-src.tar.gz differ
diff --git a/doc/pub/week36/ipynb/week36.ipynb b/doc/pub/week36/ipynb/week36.ipynb
index 32d4e9909..18d3f16c3 100644
--- a/doc/pub/week36/ipynb/week36.ipynb
+++ b/doc/pub/week36/ipynb/week36.ipynb
@@ -1296,7 +1296,7 @@
     "#    print(MSEPredict[i])\n",
     "    # Now plot the results\n",
     "plt.figure()\n",
-    "plt.plot(np.log10(lambdas), MSEPredict, 'r--', label = 'MSE Ridge Test')\n",
+    "plt.plot(np.log10(lambdas), MSEPredict, 'r--', label = 'MSE Ridge Train')\n",
     "plt.xlabel('log10(lambda)')\n",
     "plt.ylabel('MSE')\n",
     "plt.legend()\n",
@@ -1368,7 +1368,7 @@
     "    RegLasso = linear_model.Lasso(lmb)\n",
     "    RegLasso.fit(X,y)\n",
     "    ypredictLasso = RegLasso.predict(X)\n",
-    "    print(RegLasso_coef_)\n",
+    "    print(RegLasso.coef_)\n",
     "    MSELassoPredict[i] = MSE(y,ypredictLasso)\n",
     "# Now plot the results\n",
     "plt.figure()\n",
diff --git a/doc/src/week36/week36.do.txt b/doc/src/week36/week36.do.txt
index 99196f716..ac81f980b 100644
--- a/doc/src/week36/week36.do.txt
+++ b/doc/src/week36/week36.do.txt
@@ -737,7 +737,7 @@ for i in range(nlambdas):
 #    print(MSEPredict[i])
     # Now plot the results
 plt.figure()
-plt.plot(np.log10(lambdas), MSEPredict, 'r--', label = 'MSE Ridge Test')
+plt.plot(np.log10(lambdas), MSEPredict, 'r--', label = 'MSE Ridge Train')
 plt.xlabel('log10(lambda)')
 plt.ylabel('MSE')
 plt.legend()
@@ -798,7 +798,7 @@ for i in range(nlambdas):
     RegLasso = linear_model.Lasso(lmb)
     RegLasso.fit(X,y)
     ypredictLasso = RegLasso.predict(X)
-    print(RegLasso_coef_)
+    print(RegLasso.coef_)
     MSELassoPredict[i] = MSE(y,ypredictLasso)
 # Now plot the results
 plt.figure()