diff --git a/ml1/2_8_Conclusions.ipynb b/ml1/2_8_Conclusions.ipynb
index f5fbfec..3145e25 100644
--- a/ml1/2_8_Conclusions.ipynb
+++ b/ml1/2_8_Conclusions.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "![](files/images/EscUpmPolit_p.gif \"UPM\")"
+    "![](./images/EscUpmPolit_p.gif \"UPM\")"
    ]
   },
   {
@@ -52,7 +52,7 @@
     "\n",
     "Particularly in high-dimensional spaces, data can more easily be separated linearly and the simplicity of classifiers such as naive Bayes and linear SVMs might lead to better generalization than is achieved by other classifiers.\n",
     "\n",
-    "The plots show training points in solid colors and testing points semi-transparent. The lower right shows the classification accuracy on the test set.\n",
+    "The plots show training points in solid colors and testing points in semi-transparent colors. The lower right shows the classification accuracy on the test set.\n",
     "\n",
     "The [DummyClassifier](http://scikit-learn.org/stable/modules/generated/sklearn.dummy.DummyClassifier.html#sklearn.dummy.DummyClassifier) is a classifier that makes predictions using simple rules. It is useful as a simple baseline to compare with other (real) classifiers. \n",
     "\n",
@@ -94,7 +94,7 @@
    "metadata": {},
    "source": [
     "## Licence\n",
-    "The notebook is freely licensed under under the [Creative Commons Attribution Share-Alike license](https://creativecommons.org/licenses/by/2.0/).  \n",
+    "The notebook is freely licensed under the [Creative Commons Attribution Share-Alike license](https://creativecommons.org/licenses/by/2.0/).  \n",
     "\n",
     "©  Carlos A. Iglesias, Universidad Politécnica de Madrid."
    ]