From 997118dd68ab86087f1fe6540155ba32d0019a5f Mon Sep 17 00:00:00 2001
From: Morten Hjorth-Jensen <morten.hjorth-jensen@fys.uio.no>
Date: Tue, 6 Sep 2022 09:00:52 +0200
Subject: [PATCH] cleaning up typos

---
 .../2022/Project1/html/._Project1-bs000.html  |   6 +-
 .../2022/Project1/html/Project1-bs.html       |   6 +-
 doc/Projects/2022/Project1/html/Project1.html |   6 +-
 .../2022/Project1/ipynb/Project1.ipynb        | 106 +++++++++---------
 .../Project1/ipynb/ipynb-Project1-src.tar.gz  | Bin 193 -> 193 bytes
 doc/Projects/2022/Project1/pdf/Project1.p.tex |   6 +-
 doc/Projects/2022/Project1/pdf/Project1.pdf   | Bin 254161 -> 254161 bytes
 doc/Projects/2022/Project1/pdf/Project1.tex   |   6 +-
 .../Projects/2022/Project1/Project1.do.txt    |   4 +-
 9 files changed, 70 insertions(+), 70 deletions(-)

diff --git a/doc/Projects/2022/Project1/html/._Project1-bs000.html b/doc/Projects/2022/Project1/html/._Project1-bs000.html
index 27a4b8847..affba1fe4 100644
--- a/doc/Projects/2022/Project1/html/._Project1-bs000.html
+++ b/doc/Projects/2022/Project1/html/._Project1-bs000.html
@@ -162,7 +162,7 @@ MathJax.Hub.Config({
 </center>
 <br>
 <center>
-<h4>Sep 5, 2022</h4>
+<h4>Sep 6, 2022</h4>
 </center> <!-- date -->
 <br>
 
@@ -171,7 +171,7 @@ MathJax.Hub.Config({
 <h2 id="regression-analysis-and-resampling-methods" class="anchor">Regression analysis and resampling methods  </h2>
 
 <p>The main aim of this project is to study in more detail various
-regression methods, including the Ordinary Least Squares (OLS) method,
+regression methods, including the Ordinary Least Squares (OLS) method.
 In addition to the scientific part, in this course we want also to
 give you an experience in writing scientific reports.  The format for
 the delivery of your answers is namely that of a scientific report. At
@@ -189,7 +189,7 @@ recommend to do the code development and testing with a simpler
 one-dimensional function, similar to those discussed in the exercises
 of week 35. A simple test, as discussed during the lectures the first
 two weeks is to set the design matrix equal to the identity
-matrix. Then our model should give a mean square error which is exactly equal to zero.
+matrix. Then your model should give a mean square error which is exactly equal to zero.
 When you are sure that your codes function well, you can then replace
 the one-dimensional test function with the two-dimensional <b>Franke</b> function
 discussed here.
diff --git a/doc/Projects/2022/Project1/html/Project1-bs.html b/doc/Projects/2022/Project1/html/Project1-bs.html
index 27a4b8847..affba1fe4 100644
--- a/doc/Projects/2022/Project1/html/Project1-bs.html
+++ b/doc/Projects/2022/Project1/html/Project1-bs.html
@@ -162,7 +162,7 @@ MathJax.Hub.Config({
 </center>
 <br>
 <center>
-<h4>Sep 5, 2022</h4>
+<h4>Sep 6, 2022</h4>
 </center> <!-- date -->
 <br>
 
@@ -171,7 +171,7 @@ MathJax.Hub.Config({
 <h2 id="regression-analysis-and-resampling-methods" class="anchor">Regression analysis and resampling methods  </h2>
 
 <p>The main aim of this project is to study in more detail various
-regression methods, including the Ordinary Least Squares (OLS) method,
+regression methods, including the Ordinary Least Squares (OLS) method.
 In addition to the scientific part, in this course we want also to
 give you an experience in writing scientific reports.  The format for
 the delivery of your answers is namely that of a scientific report. At
@@ -189,7 +189,7 @@ recommend to do the code development and testing with a simpler
 one-dimensional function, similar to those discussed in the exercises
 of week 35. A simple test, as discussed during the lectures the first
 two weeks is to set the design matrix equal to the identity
-matrix. Then our model should give a mean square error which is exactly equal to zero.
+matrix. Then your model should give a mean square error which is exactly equal to zero.
 When you are sure that your codes function well, you can then replace
 the one-dimensional test function with the two-dimensional <b>Franke</b> function
 discussed here.
diff --git a/doc/Projects/2022/Project1/html/Project1.html b/doc/Projects/2022/Project1/html/Project1.html
index e62ff2afa..3230fa730 100644
--- a/doc/Projects/2022/Project1/html/Project1.html
+++ b/doc/Projects/2022/Project1/html/Project1.html
@@ -201,13 +201,13 @@ MathJax.Hub.Config({
 </center>
 <br>
 <center>
-<h4>Sep 5, 2022</h4>
+<h4>Sep 6, 2022</h4>
 </center> <!-- date -->
 <br>
 <h2 id="regression-analysis-and-resampling-methods">Regression analysis and resampling methods  </h2>
 
 <p>The main aim of this project is to study in more detail various
-regression methods, including the Ordinary Least Squares (OLS) method,
+regression methods, including the Ordinary Least Squares (OLS) method.
 In addition to the scientific part, in this course we want also to
 give you an experience in writing scientific reports.  The format for
 the delivery of your answers is namely that of a scientific report. At
@@ -225,7 +225,7 @@ recommend to do the code development and testing with a simpler
 one-dimensional function, similar to those discussed in the exercises
 of week 35. A simple test, as discussed during the lectures the first
 two weeks is to set the design matrix equal to the identity
-matrix. Then our model should give a mean square error which is exactly equal to zero.
+matrix. Then your model should give a mean square error which is exactly equal to zero.
 When you are sure that your codes function well, you can then replace
 the one-dimensional test function with the two-dimensional <b>Franke</b> function
 discussed here.
diff --git a/doc/Projects/2022/Project1/ipynb/Project1.ipynb b/doc/Projects/2022/Project1/ipynb/Project1.ipynb
index e45c271d8..3af46c0ae 100644
--- a/doc/Projects/2022/Project1/ipynb/Project1.ipynb
+++ b/doc/Projects/2022/Project1/ipynb/Project1.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "7a2ac097",
+   "id": "f3a8c4d6",
    "metadata": {
     "editable": true
    },
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4c81032a",
+   "id": "ba2f6e4e",
    "metadata": {
     "editable": true
    },
@@ -22,12 +22,12 @@
     "# Project 1 on Machine Learning, deadline October 7, 2022\n",
     "**[Data Analysis and Machine Learning FYS-STK3155/FYS4155](http://www.uio.no/studier/emner/matnat/fys/FYS3155/index-eng.html)**, University of Oslo, Norway\n",
     "\n",
-    "Date: **Sep 5, 2022**"
+    "Date: **Sep 6, 2022**"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "3a6a8595",
+   "id": "e7d1ae4f",
    "metadata": {
     "editable": true
    },
@@ -35,7 +35,7 @@
     "## Regression analysis and resampling methods\n",
     "\n",
     "The main aim of this project is to study in more detail various\n",
-    "regression methods, including the Ordinary Least Squares (OLS) method,\n",
+    "regression methods, including the Ordinary Least Squares (OLS) method.\n",
     "In addition to the scientific part, in this course we want also to\n",
     "give you an experience in writing scientific reports.  The format for\n",
     "the delivery of your answers is namely that of a scientific report. At\n",
@@ -52,7 +52,7 @@
     "one-dimensional function, similar to those discussed in the exercises\n",
     "of week 35. A simple test, as discussed during the lectures the first\n",
     "two weeks is to set the design matrix equal to the identity\n",
-    "matrix. Then our model should give a mean square error which is exactly equal to zero.\n",
+    "matrix. Then your model should give a mean square error which is exactly equal to zero.\n",
     "When you are sure that your codes function well, you can then replace\n",
     "the one-dimensional test function with the two-dimensional **Franke** function\n",
     "discussed here.\n",
@@ -63,7 +63,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "612a16af",
+   "id": "8524af72",
    "metadata": {
     "editable": true
    },
@@ -85,7 +85,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9acb8af9",
+   "id": "67acaf3f",
    "metadata": {
     "editable": true
    },
@@ -100,7 +100,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1760b791",
+   "id": "7fbfb83f",
    "metadata": {
     "editable": true
    },
@@ -129,7 +129,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "0887069d",
+   "id": "365c9b12",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -181,7 +181,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6ba1eed9",
+   "id": "42bf4d8c",
    "metadata": {
     "editable": true
    },
@@ -197,7 +197,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b8977dc1",
+   "id": "1a97a8a9",
    "metadata": {
     "editable": true
    },
@@ -209,7 +209,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "97dbce3f",
+   "id": "005a34cd",
    "metadata": {
     "editable": true
    },
@@ -220,7 +220,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "918c0cbb",
+   "id": "f5cba6b7",
    "metadata": {
     "editable": true
    },
@@ -232,7 +232,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "12ed8d76",
+   "id": "c614fcd7",
    "metadata": {
     "editable": true
    },
@@ -244,7 +244,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "dde5fd1a",
+   "id": "d05b6889",
    "metadata": {
     "editable": true
    },
@@ -256,7 +256,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5ab0b041",
+   "id": "16138919",
    "metadata": {
     "editable": true
    },
@@ -267,7 +267,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d10e8fa5",
+   "id": "bc66b35b",
    "metadata": {
     "editable": true
    },
@@ -279,7 +279,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4bde13fb",
+   "id": "4eb37340",
    "metadata": {
     "editable": true
    },
@@ -292,7 +292,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8635bca3",
+   "id": "325b1020",
    "metadata": {
     "editable": true
    },
@@ -304,7 +304,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "da21e635",
+   "id": "df636f58",
    "metadata": {
     "editable": true
    },
@@ -314,7 +314,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "62ce1847",
+   "id": "7362a90c",
    "metadata": {
     "editable": true
    },
@@ -326,7 +326,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8b985826",
+   "id": "4a23d9aa",
    "metadata": {
     "editable": true
    },
@@ -337,7 +337,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1c015e08",
+   "id": "048427bb",
    "metadata": {
     "editable": true
    },
@@ -359,7 +359,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ea1b5d0b",
+   "id": "5798da61",
    "metadata": {
     "editable": true
    },
@@ -372,7 +372,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "362e556a",
+   "id": "dabdfbc1",
    "metadata": {
     "editable": true
    },
@@ -384,7 +384,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e5eeda54",
+   "id": "6f83ef69",
    "metadata": {
     "editable": true
    },
@@ -396,7 +396,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "70012504",
+   "id": "fd117767",
    "metadata": {
     "editable": true
    },
@@ -406,7 +406,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8d234f27",
+   "id": "36d8ba67",
    "metadata": {
     "editable": true
    },
@@ -418,7 +418,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3460f330",
+   "id": "277e8cbd",
    "metadata": {
     "editable": true
    },
@@ -447,7 +447,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2b0214ff",
+   "id": "e0056ae2",
    "metadata": {
     "editable": true
    },
@@ -479,7 +479,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ba76c42f",
+   "id": "5bea6c04",
    "metadata": {
     "editable": true
    },
@@ -491,7 +491,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cc9118d1",
+   "id": "2b233d93",
    "metadata": {
     "editable": true
    },
@@ -510,7 +510,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f0901443",
+   "id": "bbfe79b1",
    "metadata": {
     "editable": true
    },
@@ -522,7 +522,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "128dfd18",
+   "id": "f6b6ef4e",
    "metadata": {
     "editable": true
    },
@@ -536,7 +536,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e5ff09e8",
+   "id": "d42ac463",
    "metadata": {
     "editable": true
    },
@@ -548,7 +548,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a39514b2",
+   "id": "93d7fb47",
    "metadata": {
     "editable": true
    },
@@ -558,7 +558,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4c34a548",
+   "id": "9e03ac19",
    "metadata": {
     "editable": true
    },
@@ -570,7 +570,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "300bde6a",
+   "id": "c1a62cd8",
    "metadata": {
     "editable": true
    },
@@ -580,7 +580,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "71a2c51a",
+   "id": "2ceb482f",
    "metadata": {
     "editable": true
    },
@@ -592,7 +592,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f7e980d0",
+   "id": "61d409d6",
    "metadata": {
     "editable": true
    },
@@ -611,7 +611,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ef87f011",
+   "id": "d5b3b111",
    "metadata": {
     "editable": true
    },
@@ -636,7 +636,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1288c49d",
+   "id": "19411bb1",
    "metadata": {
     "editable": true
    },
@@ -656,7 +656,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8ba58fed",
+   "id": "33c43b4e",
    "metadata": {
     "editable": true
    },
@@ -673,7 +673,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4b4db7cc",
+   "id": "1daf2ad3",
    "metadata": {
     "editable": true
    },
@@ -701,7 +701,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "daf3d605",
+   "id": "26959ad8",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -713,7 +713,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "25e4e3c2",
+   "id": "4cb0aeb9",
    "metadata": {
     "editable": true
    },
@@ -725,7 +725,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "045af476",
+   "id": "15a9a7ad",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -751,7 +751,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "44ca47a4",
+   "id": "1ca366f6",
    "metadata": {
     "editable": true
    },
@@ -776,7 +776,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0bff19b9",
+   "id": "ed16fcae",
    "metadata": {
     "editable": true
    },
@@ -790,7 +790,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f244210d",
+   "id": "a10f8033",
    "metadata": {
     "editable": true
    },
@@ -820,7 +820,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a44b37da",
+   "id": "04989dae",
    "metadata": {
     "editable": true
    },
@@ -842,7 +842,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "36139a4b",
+   "id": "df183f51",
    "metadata": {
     "editable": true
    },
diff --git a/doc/Projects/2022/Project1/ipynb/ipynb-Project1-src.tar.gz b/doc/Projects/2022/Project1/ipynb/ipynb-Project1-src.tar.gz
index 54c7d870b08b5fa8ba98808a3ea89e6e642d4844..68e17223f652b39a89cca2070ca1296f13b620a7 100644
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diff --git a/doc/Projects/2022/Project1/pdf/Project1.p.tex b/doc/Projects/2022/Project1/pdf/Project1.p.tex
index 2a080cd07..37f743039 100644
--- a/doc/Projects/2022/Project1/pdf/Project1.p.tex
+++ b/doc/Projects/2022/Project1/pdf/Project1.p.tex
@@ -132,7 +132,7 @@ Project 1 on Machine Learning, deadline October 7, 2022
 
 % --- begin date ---
 \begin{center}
-Sep 5, 2022
+Sep 6, 2022
 \end{center}
 % --- end date ---
 
@@ -142,7 +142,7 @@ Sep 5, 2022
 \subsection{Regression analysis and resampling methods}
 
 The main aim of this project is to study in more detail various
-regression methods, including the Ordinary Least Squares (OLS) method,
+regression methods, including the Ordinary Least Squares (OLS) method.
 In addition to the scientific part, in this course we want also to
 give you an experience in writing scientific reports.  The format for
 the delivery of your answers is namely that of a scientific report. At
@@ -159,7 +159,7 @@ recommend to do the code development and testing with a simpler
 one-dimensional function, similar to those discussed in the exercises
 of week 35. A simple test, as discussed during the lectures the first
 two weeks is to set the design matrix equal to the identity
-matrix. Then our model should give a mean square error which is exactly equal to zero.
+matrix. Then your model should give a mean square error which is exactly equal to zero.
 When you are sure that your codes function well, you can then replace
 the one-dimensional test function with the two-dimensional \textbf{Franke} function
 discussed here.
diff --git a/doc/Projects/2022/Project1/pdf/Project1.pdf b/doc/Projects/2022/Project1/pdf/Project1.pdf
index c39dde934601b14fdca63d51f07a5188c2e630c1..19452bc03c5a4a2c83f1eee9b98dcdee178f6554 100644
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diff --git a/doc/Projects/2022/Project1/pdf/Project1.tex b/doc/Projects/2022/Project1/pdf/Project1.tex
index c7a997eb9..f75247234 100644
--- a/doc/Projects/2022/Project1/pdf/Project1.tex
+++ b/doc/Projects/2022/Project1/pdf/Project1.tex
@@ -102,7 +102,7 @@ Project 1 on Machine Learning, deadline October 7, 2022
 
 % --- begin date ---
 \begin{center}
-Sep 5, 2022
+Sep 6, 2022
 \end{center}
 % --- end date ---
 
@@ -112,7 +112,7 @@ Sep 5, 2022
 \subsection*{Regression analysis and resampling methods}
 
 The main aim of this project is to study in more detail various
-regression methods, including the Ordinary Least Squares (OLS) method,
+regression methods, including the Ordinary Least Squares (OLS) method.
 In addition to the scientific part, in this course we want also to
 give you an experience in writing scientific reports.  The format for
 the delivery of your answers is namely that of a scientific report. At
@@ -129,7 +129,7 @@ recommend to do the code development and testing with a simpler
 one-dimensional function, similar to those discussed in the exercises
 of week 35. A simple test, as discussed during the lectures the first
 two weeks is to set the design matrix equal to the identity
-matrix. Then our model should give a mean square error which is exactly equal to zero.
+matrix. Then your model should give a mean square error which is exactly equal to zero.
 When you are sure that your codes function well, you can then replace
 the one-dimensional test function with the two-dimensional \textbf{Franke} function
 discussed here.
diff --git a/doc/src/Projects/2022/Project1/Project1.do.txt b/doc/src/Projects/2022/Project1/Project1.do.txt
index 02837463c..3aa99f31c 100644
--- a/doc/src/Projects/2022/Project1/Project1.do.txt
+++ b/doc/src/Projects/2022/Project1/Project1.do.txt
@@ -9,7 +9,7 @@ DATE: today
 
 
 The main aim of this project is to study in more detail various
-regression methods, including the Ordinary Least Squares (OLS) method,
+regression methods, including the Ordinary Least Squares (OLS) method.
 In addition to the scientific part, in this course we want also to
 give you an experience in writing scientific reports.  The format for
 the delivery of your answers is namely that of a scientific report. At
@@ -27,7 +27,7 @@ recommend to do the code development and testing with a simpler
 one-dimensional function, similar to those discussed in the exercises
 of week 35. A simple test, as discussed during the lectures the first
 two weeks is to set the design matrix equal to the identity
-matrix. Then our model should give a mean square error which is exactly equal to zero.
+matrix. Then your model should give a mean square error which is exactly equal to zero.
 When you are sure that your codes function well, you can then replace
 the one-dimensional test function with the two-dimensional _Franke_ function
 discussed here.