diff --git a/doc/Projects/2021/Project3/html/._Project3-bs000.html b/doc/Projects/2021/Project3/html/._Project3-bs000.html
index 1144eb817..dccf24e20 100644
--- a/doc/Projects/2021/Project3/html/._Project3-bs000.html
+++ b/doc/Projects/2021/Project3/html/._Project3-bs000.html
@@ -359,7 +359,7 @@ cons of the various methods. Are there some methods which provide both
 low variance and low bias?
 </p>
 
-<p><b>Hint</b>: when you use different methods, pay attention to how you represent (and understand) the complexity of the model. For for example decision trees, this is represented by the depth of the tree. </p>
+<p><b>Hint</b>: when you use different methods, pay attention to how you represent (and understand) the complexity of the model. For example, when using  decision trees you may  represent the complexity of your model  by the depth of the tree. </p>
 <h2 id="introduction-to-numerical-projects" class="anchor">Introduction to numerical projects </h2>
 
 <p>Here follows a brief recipe and recommendation on how to write a report for each
diff --git a/doc/Projects/2021/Project3/html/Project3-bs.html b/doc/Projects/2021/Project3/html/Project3-bs.html
index 1144eb817..dccf24e20 100644
--- a/doc/Projects/2021/Project3/html/Project3-bs.html
+++ b/doc/Projects/2021/Project3/html/Project3-bs.html
@@ -359,7 +359,7 @@ cons of the various methods. Are there some methods which provide both
 low variance and low bias?
 </p>
 
-<p><b>Hint</b>: when you use different methods, pay attention to how you represent (and understand) the complexity of the model. For for example decision trees, this is represented by the depth of the tree. </p>
+<p><b>Hint</b>: when you use different methods, pay attention to how you represent (and understand) the complexity of the model. For example, when using  decision trees you may  represent the complexity of your model  by the depth of the tree. </p>
 <h2 id="introduction-to-numerical-projects" class="anchor">Introduction to numerical projects </h2>
 
 <p>Here follows a brief recipe and recommendation on how to write a report for each
diff --git a/doc/Projects/2021/Project3/html/Project3.html b/doc/Projects/2021/Project3/html/Project3.html
index 2e06fadd8..5fe0f289b 100644
--- a/doc/Projects/2021/Project3/html/Project3.html
+++ b/doc/Projects/2021/Project3/html/Project3.html
@@ -390,7 +390,7 @@ cons of the various methods. Are there some methods which provide both
 low variance and low bias?
 </p>
 
-<p><b>Hint</b>: when you use different methods, pay attention to how you represent (and understand) the complexity of the model. For for example decision trees, this is represented by the depth of the tree. </p>
+<p><b>Hint</b>: when you use different methods, pay attention to how you represent (and understand) the complexity of the model. For example, when using  decision trees you may  represent the complexity of your model  by the depth of the tree. </p>
 <h2 id="introduction-to-numerical-projects">Introduction to numerical projects </h2>
 
 <p>Here follows a brief recipe and recommendation on how to write a report for each
diff --git a/doc/Projects/2021/Project3/ipynb/Project3.ipynb b/doc/Projects/2021/Project3/ipynb/Project3.ipynb
index 7d98fd7d5..3fb613d09 100644
--- a/doc/Projects/2021/Project3/ipynb/Project3.ipynb
+++ b/doc/Projects/2021/Project3/ipynb/Project3.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "26d52fd9",
+   "id": "e6c08da8",
    "metadata": {
     "editable": true
    },
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "236f6cfd",
+   "id": "0309e266",
    "metadata": {
     "editable": true
    },
@@ -29,7 +29,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1d3c512a",
+   "id": "cedebbe4",
    "metadata": {
     "editable": true
    },
@@ -39,7 +39,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4f7124c2",
+   "id": "9038e49a",
    "metadata": {
     "editable": true
    },
@@ -79,7 +79,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ae4474c6",
+   "id": "89190c80",
    "metadata": {
     "editable": true
    },
@@ -91,7 +91,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "657d3638",
+   "id": "b2944795",
    "metadata": {
     "editable": true
    },
@@ -103,7 +103,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cd7e6b5c",
+   "id": "5d7f5f66",
    "metadata": {
     "editable": true
    },
@@ -115,7 +115,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "05c0260c",
+   "id": "55083a27",
    "metadata": {
     "editable": true
    },
@@ -127,7 +127,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9108ddbb",
+   "id": "26bb3996",
    "metadata": {
     "editable": true
    },
@@ -139,7 +139,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4e2b05cf",
+   "id": "99cbbdf4",
    "metadata": {
     "editable": true
    },
@@ -151,7 +151,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e45fc3b7",
+   "id": "1cf8305f",
    "metadata": {
     "editable": true
    },
@@ -171,7 +171,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f036e12d",
+   "id": "c76618e8",
    "metadata": {
     "editable": true
    },
@@ -185,7 +185,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "52660f41",
+   "id": "ac2c5732",
    "metadata": {
     "editable": true
    },
@@ -197,7 +197,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c1fe35cf",
+   "id": "ead9d520",
    "metadata": {
     "editable": true
    },
@@ -207,7 +207,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a1395ad8",
+   "id": "8db95bf3",
    "metadata": {
     "editable": true
    },
@@ -219,7 +219,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "aa6df14a",
+   "id": "2f93712e",
    "metadata": {
     "editable": true
    },
@@ -229,7 +229,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "09d87b1d",
+   "id": "62a0980a",
    "metadata": {
     "editable": true
    },
@@ -241,7 +241,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1dc28a4b",
+   "id": "28f54a78",
    "metadata": {
     "editable": true
    },
@@ -252,7 +252,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9e6804ed",
+   "id": "e0068e8b",
    "metadata": {
     "editable": true
    },
@@ -264,7 +264,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "004eed40",
+   "id": "f9ae2916",
    "metadata": {
     "editable": true
    },
@@ -274,7 +274,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "877b7ed0",
+   "id": "88e71606",
    "metadata": {
     "editable": true
    },
@@ -286,7 +286,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cb45cb03",
+   "id": "69bc12e7",
    "metadata": {
     "editable": true
    },
@@ -299,7 +299,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fe999d48",
+   "id": "fa2123d5",
    "metadata": {
     "editable": true
    },
@@ -311,7 +311,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f6ff7ece",
+   "id": "27474b17",
    "metadata": {
     "editable": true
    },
@@ -321,7 +321,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "40735cb1",
+   "id": "1c4da408",
    "metadata": {
     "editable": true
    },
@@ -333,7 +333,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1464be77",
+   "id": "06021617",
    "metadata": {
     "editable": true
    },
@@ -343,7 +343,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ed9d7c03",
+   "id": "b845d906",
    "metadata": {
     "editable": true
    },
@@ -355,7 +355,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "588fde58",
+   "id": "6c3956bc",
    "metadata": {
     "editable": true
    },
@@ -366,7 +366,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4fe15315",
+   "id": "15d51aa1",
    "metadata": {
     "editable": true
    },
@@ -382,7 +382,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7fcf0aab",
+   "id": "356b0ce1",
    "metadata": {
     "editable": true
    },
@@ -399,7 +399,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3f519e6a",
+   "id": "5254f0ec",
    "metadata": {
     "editable": true
    },
@@ -415,7 +415,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f1037588",
+   "id": "fb586020",
    "metadata": {
     "editable": true
    },
@@ -427,7 +427,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3a26e170",
+   "id": "8f43137a",
    "metadata": {
     "editable": true
    },
@@ -457,12 +457,12 @@
     "cons of the various methods. Are there some methods which provide both\n",
     "low variance and low bias?\n",
     "\n",
-    "**Hint**: when you use different methods, pay attention to how you represent (and understand) the complexity of the model. For for example decision trees, this is represented by the depth of the tree."
+    "**Hint**: when you use different methods, pay attention to how you represent (and understand) the complexity of the model. For example, when using  decision trees you may  represent the complexity of your model  by the depth of the tree."
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "4c14d063",
+   "id": "5efcf1de",
    "metadata": {
     "editable": true
    },
@@ -493,7 +493,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f565fe9e",
+   "id": "e53cd89a",
    "metadata": {
     "editable": true
    },
@@ -515,7 +515,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a762ce82",
+   "id": "f1b49648",
    "metadata": {
     "editable": true
    },
diff --git a/doc/Projects/2021/Project3/ipynb/ipynb-Project3-src.tar.gz b/doc/Projects/2021/Project3/ipynb/ipynb-Project3-src.tar.gz
index 857624d16..c9332ae71 100644
Binary files a/doc/Projects/2021/Project3/ipynb/ipynb-Project3-src.tar.gz and b/doc/Projects/2021/Project3/ipynb/ipynb-Project3-src.tar.gz differ
diff --git a/doc/Projects/2021/Project3/pdf/Project3.p.tex b/doc/Projects/2021/Project3/pdf/Project3.p.tex
index f3d65ee30..03a195fde 100644
--- a/doc/Projects/2021/Project3/pdf/Project3.p.tex
+++ b/doc/Projects/2021/Project3/pdf/Project3.p.tex
@@ -329,7 +329,7 @@ of your model.  Comment and discuss the results. Discuss the pros and
 cons of the various methods. Are there some methods which provide both
 low variance and low bias?
 
-\textbf{Hint}: when you use different methods, pay attention to how you represent (and understand) the complexity of the model. For for example decision trees, this is represented by the depth of the tree. 
+\textbf{Hint}: when you use different methods, pay attention to how you represent (and understand) the complexity of the model. For example, when using  decision trees you may  represent the complexity of your model  by the depth of the tree. 
 
 \subsection{Introduction to numerical projects}
 
diff --git a/doc/Projects/2021/Project3/pdf/Project3.pdf b/doc/Projects/2021/Project3/pdf/Project3.pdf
index 0c940663d..11b9f8821 100644
Binary files a/doc/Projects/2021/Project3/pdf/Project3.pdf and b/doc/Projects/2021/Project3/pdf/Project3.pdf differ
diff --git a/doc/Projects/2021/Project3/pdf/Project3.tex b/doc/Projects/2021/Project3/pdf/Project3.tex
index b9caeb691..c436aa4e3 100644
--- a/doc/Projects/2021/Project3/pdf/Project3.tex
+++ b/doc/Projects/2021/Project3/pdf/Project3.tex
@@ -303,7 +303,7 @@ of your model.  Comment and discuss the results. Discuss the pros and
 cons of the various methods. Are there some methods which provide both
 low variance and low bias?
 
-\textbf{Hint}: when you use different methods, pay attention to how you represent (and understand) the complexity of the model. For for example decision trees, this is represented by the depth of the tree. 
+\textbf{Hint}: when you use different methods, pay attention to how you represent (and understand) the complexity of the model. For example, when using  decision trees you may  represent the complexity of your model  by the depth of the tree. 
 
 \subsection*{Introduction to numerical projects}
 
diff --git a/doc/src/Projects/2021/Project3/Project3.do.txt b/doc/src/Projects/2021/Project3/Project3.do.txt
index 86512bdd8..f4a7dfd22 100644
--- a/doc/src/Projects/2021/Project3/Project3.do.txt
+++ b/doc/src/Projects/2021/Project3/Project3.do.txt
@@ -196,7 +196,7 @@ of your model.  Comment and discuss the results. Discuss the pros and
 cons of the various methods. Are there some methods which provide both
 low variance and low bias?
 
-_Hint_: when you use different methods, pay attention to how you represent (and understand) the complexity of the model. For for example decision trees, this is represented by the depth of the tree. 
+_Hint_: when you use different methods, pay attention to how you represent (and understand) the complexity of the model. For example, when using  decision trees you may  represent the complexity of your model  by the depth of the tree.