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Morten Hjorth-Jensen
2021-09-13 15:21:30 +02:00
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@@ -139,17 +139,17 @@
<ul class="nav bd-sidenav">
<li class="toctree-l1">
<a class="reference internal" href="chapter1.html">
3. Linear Regression, basic Elements
3. Linear Regression
</a>
</li>
<li class="toctree-l1">
<a class="reference internal" href="chapter2.html">
4. Resampling Methods
4. Ridge and Lasso Regression
</a>
</li>
<li class="toctree-l1">
<a class="reference internal" href="chapter3.html">
5. Ridge and Lasso Regression
5. Resampling Methods
</a>
</li>
<li class="toctree-l1">
@@ -157,9 +157,14 @@
6. Logistic Regression
</a>
</li>
<li class="toctree-l1">
<a class="reference internal" href="chapteroptimization.html">
7. Optimization, the central part of any Machine Learning algortithm
</a>
</li>
<li class="toctree-l1">
<a class="reference internal" href="chapter5.html">
7. Support Vector Machines, overarching aims
8. Support Vector Machines, overarching aims
</a>
</li>
</ul>
@@ -171,12 +176,12 @@
<ul class="nav bd-sidenav">
<li class="toctree-l1">
<a class="reference internal" href="chapter6.html">
8. Decision trees, overarching aims
9. Decision trees, overarching aims
</a>
</li>
<li class="toctree-l1">
<a class="reference internal" href="chapter7.html">
9. Ensemble Methods: From a Single Tree to Many Trees and Extreme Boosting, Meet the Jungle of Methods
10. Ensemble Methods: From a Single Tree to Many Trees and Extreme Boosting, Meet the Jungle of Methods
</a>
</li>
</ul>
@@ -188,12 +193,12 @@
<ul class="nav bd-sidenav">
<li class="toctree-l1">
<a class="reference internal" href="chapter8.html">
10. Basic ideas of the Principal Component Analysis (PCA)
11. Basic ideas of the Principal Component Analysis (PCA)
</a>
</li>
<li class="toctree-l1">
<a class="reference internal" href="Clustering.html">
11. Clustering Analysis
12. Clustering Analysis
</a>
</li>
</ul>
@@ -205,12 +210,12 @@
<ul class="nav bd-sidenav">
<li class="toctree-l1">
<a class="reference internal" href="chapter9.html">
12. Neural networks
13. Neural networks
</a>
</li>
<li class="toctree-l1">
<a class="reference internal" href="chapter10.html">
13. Building a Feed Forward Neural Network
14. Building a Feed Forward Neural Network
</a>
</li>
</ul>
@@ -290,78 +295,78 @@
</a>
<ul class="nav section-nav flex-column">
<li class="toc-h3 nav-item toc-entry">
<a class="reference internal nav-link" href="#week-35-august-23-27">
Week 35 August 23-27
<a class="reference internal nav-link" href="#week-34-august-23-27">
Week 34 August 23-27
</a>
</li>
<li class="toc-h3 nav-item toc-entry">
<a class="reference internal nav-link" href="#week-36-august-30-september-3">
Week 36 August 30-September 3
<a class="reference internal nav-link" href="#week-35-august-30-september-3">
Week 35 August 30-September 3
</a>
</li>
<li class="toc-h3 nav-item toc-entry">
<a class="reference internal nav-link" href="#week-37-september-6-10">
Week 37 September 6-10
<a class="reference internal nav-link" href="#week-36-september-6-10">
Week 36 September 6-10
</a>
</li>
<li class="toc-h3 nav-item toc-entry">
<a class="reference internal nav-link" href="#week-38-september-13-17">
Week 38 September 13-17
<a class="reference internal nav-link" href="#week-37-september-13-17">
Week 37 September 13-17
</a>
</li>
<li class="toc-h3 nav-item toc-entry">
<a class="reference internal nav-link" href="#week-39-september-20-24">
Week 39 September 20-24
<a class="reference internal nav-link" href="#week-38-september-20-24">
Week 38 September 20-24
</a>
</li>
<li class="toc-h3 nav-item toc-entry">
<a class="reference internal nav-link" href="#week-40-september-27-october-1">
Week 40 September 27- October 1
<a class="reference internal nav-link" href="#week-39-september-27-october-1">
Week 39 September 27- October 1
</a>
</li>
<li class="toc-h3 nav-item toc-entry">
<a class="reference internal nav-link" href="#week-41-october-4-8">
Week 41 October 4-8
<a class="reference internal nav-link" href="#week-40-october-4-8">
Week 40 October 4-8
</a>
</li>
<li class="toc-h3 nav-item toc-entry">
<a class="reference internal nav-link" href="#week-42-october-11-15">
Week 42 October 11-15
<a class="reference internal nav-link" href="#week-41-october-11-15">
Week 41 October 11-15
</a>
</li>
<li class="toc-h3 nav-item toc-entry">
<a class="reference internal nav-link" href="#week-43-october-18-22">
Week 43 October 18-22
<a class="reference internal nav-link" href="#week-42-october-18-22">
Week 42 October 18-22
</a>
</li>
<li class="toc-h3 nav-item toc-entry">
<a class="reference internal nav-link" href="#week-44-october-25-29">
Week 44 October 25-29
<a class="reference internal nav-link" href="#week-43-october-25-29">
Week 43 October 25-29
</a>
</li>
<li class="toc-h3 nav-item toc-entry">
<a class="reference internal nav-link" href="#week-45-november-1-5">
Week 45 November 1-5
<a class="reference internal nav-link" href="#week-44-november-1-5">
Week 44 November 1-5
</a>
</li>
<li class="toc-h3 nav-item toc-entry">
<a class="reference internal nav-link" href="#week-46-november-8-12">
Week 46 November 8-12
<a class="reference internal nav-link" href="#week-45-november-8-12">
Week 45 November 8-12
</a>
</li>
<li class="toc-h3 nav-item toc-entry">
<a class="reference internal nav-link" href="#week-47-november-15-19">
Week 47 November 15-19
<a class="reference internal nav-link" href="#week-46-november-15-19">
Week 46 November 15-19
</a>
</li>
<li class="toc-h3 nav-item toc-entry">
<a class="reference internal nav-link" href="#week-48-november-22-26">
Week 48 November 22-26
<a class="reference internal nav-link" href="#week-47-november-22-26">
Week 47 November 22-26
</a>
</li>
<li class="toc-h3 nav-item toc-entry">
<a class="reference internal nav-link" href="#week-49-november-29-december-2">
Week 49 November 29- December 2
<a class="reference internal nav-link" href="#week-48-november-29-december-2">
Week 48 November 29- December 2
</a>
</li>
</ul>
@@ -399,43 +404,58 @@
<li><p>HTF: Hastie, Tibshirani, and Friedman, The Elements of Statistical Learning</p></li>
<li><p>AG: Aurelien Geron, Hands‑On Machine Learning with Scikit‑Learn and TensorFlow</p></li>
</ul>
<div class="section" id="week-35-august-23-27">
<h3>Week 35 August 23-27<a class="headerlink" href="#week-35-august-23-27" title="Permalink to this headline"></a></h3>
<div class="section" id="week-34-august-23-27">
<h3>Week 34 August 23-27<a class="headerlink" href="#week-34-august-23-27" title="Permalink to this headline"></a></h3>
<ul class="simple">
<li><p>Lab Wednesday: Introduction to software and repetition of Python Programming</p></li>
<li><p>Lecture Thursday: Introduction to the course, what is Machine Learning and introduction to Linear Regression</p></li>
<li><p>Lecture Thursday: Introduction to the course, what is Machine Learning and introduction to Linear Regression.</p></li>
<li><p>Video of Lecture August 26, 2021 at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureThursdayAugust26.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureThursdayAugust26.mp4?vrtx=view-as-webpage</a></p></li>
<li><p>Lecture Friday: Basics of Linear Regression</p></li>
<li><p>Reading recommendations: Refresh linear algebra, GBC chapters 1 and 2. CMB sections 1.1 and 3.1. HTF chapters 2 and 3. Install scikit-learn. See lecture notes for week 35 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a></p></li>
<li><p>Video of Lecture August 27, 2021 at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureThursdayAugust27.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureThursdayAugust27.mp4?vrtx=view-as-webpage</a></p></li>
<li><p>Reading recommendations: Refresh linear algebra, GBC chapters 1 and 2. CMB sections 1.1 and 3.1. HTF chapters 2 and 3. Install scikit-learn. See lecture notes for week 34 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a></p></li>
</ul>
</div>
<div class="section" id="week-36-august-30-september-3">
<h3>Week 36 August 30-September 3<a class="headerlink" href="#week-36-august-30-september-3" title="Permalink to this headline"></a></h3>
<div class="section" id="week-35-august-30-september-3">
<h3>Week 35 August 30-September 3<a class="headerlink" href="#week-35-august-30-september-3" title="Permalink to this headline"></a></h3>
<ul class="simple">
<li><p>Lab Wednesday:</p></li>
<li><p>Lecture Thursday: Linear Regression, from ordinary linear regression to Ridge and Lasso regression, linear algebra analysis, examples and discussions of codes</p></li>
<li><p>Lecture Friday: Linear Regression, Linear algebra and Ridge and Lasso Regression, linear algebra analysis, examples and discussions of codes</p></li>
<li><p>Reading recommendations: See lecture notes for week 36 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>. HTF chapter 3. GBC chapters 1 and and sections 3.1-3.11 and 5.1 and CMB sections 1.1 and 3.1</p></li>
<li><p>Lab Wednesday: Work on exercises 1-3 for week 35</p></li>
<li><p>Thursday: Review of ordinary Least Squares with applications and discussion of Ridge Regression and Singular Value Decomposition</p></li>
<li><p>Video of lecture Thursday at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember2.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember2.mp4?vrtx=view-as-webpage</a>”.</p></li>
<li><p>Friday: Analysis of Ridge and Lasso Regression and links with Singular Value Decomposition</p></li>
<li><p>Video of lecture Friday at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember3.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember3.mp4?vrtx=view-as-webpage</a>”</p></li>
<li><p>Reading recommendations: See lecture notes for week 35 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>. HTF chapter 3. GBC chapters 1 and and sections 3.1-3.11 and 5.1 and CMB sections 1.1 and 3.1</p></li>
</ul>
</div>
<div class="section" id="week-37-september-6-10">
<h3>Week 37 September 6-10<a class="headerlink" href="#week-37-september-6-10" title="Permalink to this headline"></a></h3>
<div class="section" id="week-36-september-6-10">
<h3>Week 36 September 6-10<a class="headerlink" href="#week-36-september-6-10" title="Permalink to this headline"></a></h3>
<ul class="simple">
<li><p>Lab Wednesday: Exercises 1 and 2 from week 36</p></li>
<li><p>Lecture Thursday: Summary from last week on SVD, Statistics, probability theory and linear regression</p></li>
<li><p>Video of Lecture <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember9.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember9.mp4?vrtx=view-as-webpage</a>”.</p></li>
<li><p>Friday: Linear Regression and links with Statistics, Resampling methods and presentation of first project.</p></li>
<li><p>Video of Lecture at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureSeptember10.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureSeptember10.mp4?vrtx=view-as-webpage</a>”</p></li>
<li><p>Recommended Reading: Lectures on Regression, Bishop 1.1, 1.2, 2.1, 2.2, 2.3 and 3.1, Hastie et al chapter 3</p></li>
</ul>
</div>
<div class="section" id="week-37-september-13-17">
<h3>Week 37 September 13-17<a class="headerlink" href="#week-37-september-13-17" title="Permalink to this headline"></a></h3>
<ul class="simple">
<li><p>Lab Wednesday:</p></li>
<li><p>Lecture Thursday: Statistical interpretation of Linear Regression</p></li>
<li><p>Lecture Friday: Bias-Variance tradeoff</p></li>
<li><p>Reading recommendations: See lecture notes for week 37 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>. GBC sections 5.2-5.5, CMB section 3.2</p>
<li><p>Lecture Thursday: Resampling methods, cross-validation and Bootstrap</p></li>
<li><p>Lecture Friday: More on Resampling methods and summary of linear regression</p></li>
<li><p>Reading recommendations: See lecture notes for week 37 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p>
<ul>
<li><p>Chapter</p></li>
</ul>
</li>
</ul>
</div>
<div class="section" id="week-38-september-13-17">
<h3>Week 38 September 13-17<a class="headerlink" href="#week-38-september-13-17" title="Permalink to this headline"></a></h3>
<div class="section" id="week-38-september-20-24">
<h3>Week 38 September 20-24<a class="headerlink" href="#week-38-september-20-24" title="Permalink to this headline"></a></h3>
<ul class="simple">
<li><p>Lab Wednesday:</p></li>
<li><p>Lecture Thursday: Resampling methods, cross-validation and Bootstrap</p></li>
<li><p>Lecture Friday: More on Resampling methods and summary of linear regression</p></li>
<li><p>Lecture Thursday: Classification problems and Logistic Regression, from binary cases to several categories</p></li>
<li><p>Lecture Friday: Logistic Regression and gradient optimization</p></li>
<li><p>Reading recommendations: See lecture notes for week 38 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p>
<ul>
<li><p>Chapter</p></li>
@@ -443,12 +463,12 @@
</li>
</ul>
</div>
<div class="section" id="week-39-september-20-24">
<h3>Week 39 September 20-24<a class="headerlink" href="#week-39-september-20-24" title="Permalink to this headline"></a></h3>
<div class="section" id="week-39-september-27-october-1">
<h3>Week 39 September 27- October 1<a class="headerlink" href="#week-39-september-27-october-1" title="Permalink to this headline"></a></h3>
<ul class="simple">
<li><p>Lab Wednesday:</p></li>
<li><p>Lecture Thursday: Classification problems and Logistic Regression, from binary cases to several categories</p></li>
<li><p>Lecture Friday: Logistic Regression and gradient optimization</p></li>
<li><p>Lecture Thursday: Gradient Optimization methods</p></li>
<li><p>Lecture Friday: Deep Learning and Neural Networks</p></li>
<li><p>Reading recommendations: See lecture notes for week 39 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p>
<ul>
<li><p>Chapter</p></li>
@@ -456,21 +476,8 @@
</li>
</ul>
</div>
<div class="section" id="week-40-september-27-october-1">
<h3>Week 40 September 27- October 1<a class="headerlink" href="#week-40-september-27-october-1" title="Permalink to this headline"></a></h3>
<ul class="simple">
<li><p>Lab Wednesday:</p></li>
<li><p>Lecture Thursday: Gradient Optimization methods</p></li>
<li><p>Lecture Friday: Deep Learning and Neural Networks</p></li>
<li><p>Reading recommendations: See lecture notes for week 40 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p>
<ul>
<li><p>Chapter</p></li>
</ul>
</li>
</ul>
</div>
<div class="section" id="week-41-october-4-8">
<h3>Week 41 October 4-8<a class="headerlink" href="#week-41-october-4-8" title="Permalink to this headline"></a></h3>
<div class="section" id="week-40-october-4-8">
<h3>Week 40 October 4-8<a class="headerlink" href="#week-40-october-4-8" title="Permalink to this headline"></a></h3>
<ul class="simple">
<li><p>Lab Wednesday:</p></li>
<li><p>Lecture Thursday: Writing a feed-forward Neural Network code for regression and classification</p></li>
@@ -482,8 +489,8 @@
</li>
</ul>
</div>
<div class="section" id="week-42-october-11-15">
<h3>Week 42 October 11-15<a class="headerlink" href="#week-42-october-11-15" title="Permalink to this headline"></a></h3>
<div class="section" id="week-41-october-11-15">
<h3>Week 41 October 11-15<a class="headerlink" href="#week-41-october-11-15" title="Permalink to this headline"></a></h3>
<ul class="simple">
<li><p>Lab Wednesday:</p></li>
<li><p>Lecture Thursday: Deep learning and Neural Networks</p></li>
@@ -495,8 +502,8 @@
</li>
</ul>
</div>
<div class="section" id="week-43-october-18-22">
<h3>Week 43 October 18-22<a class="headerlink" href="#week-43-october-18-22" title="Permalink to this headline"></a></h3>
<div class="section" id="week-42-october-18-22">
<h3>Week 42 October 18-22<a class="headerlink" href="#week-42-october-18-22" title="Permalink to this headline"></a></h3>
<ul class="simple">
<li><p>Lab Wednesday:</p></li>
<li><p>Lecture Thursday: Convolutional Neural Networks and classification problems</p></li>
@@ -508,8 +515,8 @@
</li>
</ul>
</div>
<div class="section" id="week-44-october-25-29">
<h3>Week 44 October 25-29<a class="headerlink" href="#week-44-october-25-29" title="Permalink to this headline"></a></h3>
<div class="section" id="week-43-october-25-29">
<h3>Week 43 October 25-29<a class="headerlink" href="#week-43-october-25-29" title="Permalink to this headline"></a></h3>
<ul class="simple">
<li><p>Lab Wednesday:</p></li>
<li><p>Lecture Thursday: Recurrent Neural Networks</p></li>
@@ -521,8 +528,8 @@
</li>
</ul>
</div>
<div class="section" id="week-45-november-1-5">
<h3>Week 45 November 1-5<a class="headerlink" href="#week-45-november-1-5" title="Permalink to this headline"></a></h3>
<div class="section" id="week-44-november-1-5">
<h3>Week 44 November 1-5<a class="headerlink" href="#week-44-november-1-5" title="Permalink to this headline"></a></h3>
<ul class="simple">
<li><p>Lab Wednesday:</p></li>
<li><p>Lecture Thursday: Decision trees, classification and regression</p></li>
@@ -534,8 +541,8 @@
</li>
</ul>
</div>
<div class="section" id="week-46-november-8-12">
<h3>Week 46 November 8-12<a class="headerlink" href="#week-46-november-8-12" title="Permalink to this headline"></a></h3>
<div class="section" id="week-45-november-8-12">
<h3>Week 45 November 8-12<a class="headerlink" href="#week-45-november-8-12" title="Permalink to this headline"></a></h3>
<ul class="simple">
<li><p>Lab Wednesday:</p></li>
<li><p>Lecture Thursday: Ensemble methods, bagging and random forests</p></li>
@@ -547,8 +554,8 @@
</li>
</ul>
</div>
<div class="section" id="week-47-november-15-19">
<h3>Week 47 November 15-19<a class="headerlink" href="#week-47-november-15-19" title="Permalink to this headline"></a></h3>
<div class="section" id="week-46-november-15-19">
<h3>Week 46 November 15-19<a class="headerlink" href="#week-46-november-15-19" title="Permalink to this headline"></a></h3>
<ul class="simple">
<li><p>Lab Wednesday:</p></li>
<li><p>Lecture Thursday:</p></li>
@@ -560,8 +567,8 @@
</li>
</ul>
</div>
<div class="section" id="week-48-november-22-26">
<h3>Week 48 November 22-26<a class="headerlink" href="#week-48-november-22-26" title="Permalink to this headline"></a></h3>
<div class="section" id="week-47-november-22-26">
<h3>Week 47 November 22-26<a class="headerlink" href="#week-47-november-22-26" title="Permalink to this headline"></a></h3>
<ul class="simple">
<li><p>Lab Wednesday:</p></li>
<li><p>Lecture Thursday: Unsupervised Learning, Principal Component Analysis (PCA)</p></li>
@@ -573,8 +580,8 @@
</li>
</ul>
</div>
<div class="section" id="week-49-november-29-december-2">
<h3>Week 49 November 29- December 2<a class="headerlink" href="#week-49-november-29-december-2" title="Permalink to this headline"></a></h3>
<div class="section" id="week-48-november-29-december-2">
<h3>Week 48 November 29- December 2<a class="headerlink" href="#week-48-november-29-december-2" title="Permalink to this headline"></a></h3>
<ul class="simple">
<li><p>Lab Wednesday:</p></li>
<li><p>Lecture Thursday: Unsupervised Learning and Clustering</p></li>