Morten Hjorth-Jensen
744 lines
36 KiB
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744 lines
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<h1 class="site-logo" id="site-title">Applied Data Analysis and Machine Learning</h1>
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Applied Data Analysis and Machine Learning, FYS-STK3155/4155 at the University of Oslo, Norway
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About the course
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<a class="current reference internal" href="#">
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Teaching schedule with links to material
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Teachers and Grading
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Textbooks
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Review of Statistics with Resampling Techniques and Linear Algebra
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1. Elements of Probability Theory and Statistical Data Analysis
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<a class="reference internal" href="linalg.html">
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2. Linear Algebra, Handling of Arrays and more Python Features
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From Regression to Support Vector Machines
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3. Linear Regression
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4. Ridge and Lasso Regression
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<li class="toctree-l1">
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<a class="reference internal" href="chapter3.html">
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5. Resampling Methods
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6. Logistic Regression
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<a class="reference internal" href="chapteroptimization.html">
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7. Optimization, the central part of any Machine Learning algortithm
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<a class="reference internal" href="chapter5.html">
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8. Support Vector Machines, overarching aims
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</a>
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Decision Trees, Ensemble Methods and Boosting
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9. Decision trees, overarching aims
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<li class="toctree-l1">
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<a class="reference internal" href="chapter7.html">
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10. Ensemble Methods: From a Single Tree to Many Trees and Extreme Boosting, Meet the Jungle of Methods
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Dimensionality Reduction
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11. Basic ideas of the Principal Component Analysis (PCA)
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12. Clustering Analysis
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Deep Learning Methods
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13. Neural networks
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14. Building a Feed Forward Neural Network
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15. Solving Differential Equations with Deep Learning
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Weekly Schedule
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<a class="reference internal nav-link" href="#week-34-august-23-27">
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Week 34 August 23-27
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<a class="reference internal nav-link" href="#week-35-august-30-september-3">
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Week 35 August 30-September 3
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<a class="reference internal nav-link" href="#week-36-september-6-10">
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Week 36 September 6-10
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<a class="reference internal nav-link" href="#week-37-september-13-17">
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Week 37 September 13-17
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-38-september-20-24">
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Week 38 September 20-24
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Week 39 September 27- October 1
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<a class="reference internal nav-link" href="#week-40-october-4-8">
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Week 40 October 4-8
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-41-october-11-15">
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Week 41 October 11-15
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-42-october-18-22">
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Week 42 October 18-22
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<a class="reference internal nav-link" href="#week-43-october-25-29">
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Week 43 October 25-29
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-44-november-1-5">
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Week 44 November 1-5
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-45-november-8-12">
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Week 45 November 8-12
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-46-november-15-19">
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Week 46 November 15-19
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-47-november-22-26">
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Week 47 November 22-26
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-48-november-29-december-2">
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Week 48 November 29- December 2
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<div class="section" id="teaching-schedule-with-links-to-material">
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<h1>Teaching schedule with links to material<a class="headerlink" href="#teaching-schedule-with-links-to-material" title="Permalink to this headline">¶</a></h1>
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<p>This course will be delivered in a hybrid mode, with online lectures and on site or online laboratory sessions.</p>
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<ol class="simple">
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<li><p>Four lectures per week, Fall semester, 10 ECTS. The lectures are in person but will be recorded and linked to this site and the official University of Oslo website for the course;</p></li>
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<li><p>Two hours of laboratory sessions for work on computational projects and exercises for each group. There will also be fully digital laboratory sessions for those who cannot attend;</p></li>
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<li><p>Three projects which are graded and count 1/3 each of the final grade. The deadlines for the projects are October 11 for project 1, November 15 for project 2 and December 13 for project 3.</p></li>
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<li><p>A selected number of weekly assignments;</p></li>
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<li><p>The course is part of the CS Master of Science program, but is open to other bachelor and Master of Science students at the University of Oslo;</p></li>
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<li><p>The course is offered as a FYS-MAT4155 (Master of Science level) and a FYS-MAT3155 (senior undergraduate) course;</p></li>
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<li><p>Videos of teaching material are available via the links 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>
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<li><p>Weekly emails with summary of activities will be mailed to all participants;</p></li>
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</ol>
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<div class="section" id="weekly-schedule">
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<h2>Weekly Schedule<a class="headerlink" href="#weekly-schedule" title="Permalink to this headline">¶</a></h2>
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<p>For the reading assignments we use the following abbreviations:</p>
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<ul class="simple">
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<li><p>GBC: Goodfellow, Bengio, and Courville, Deep Learning</p></li>
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<li><p>CMB: Christopher M. Bishop, Pattern Recognition and Machine Learning</p></li>
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<li><p>HTF: Hastie, Tibshirani, and Friedman, The Elements of Statistical Learning</p></li>
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<li><p>AG: Aurelien Geron, Hands‑On Machine Learning with Scikit‑Learn and TensorFlow</p></li>
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</ul>
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<div class="section" id="week-34-august-23-27">
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<h3>Week 34 August 23-27<a class="headerlink" href="#week-34-august-23-27" title="Permalink to this headline">¶</a></h3>
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<ul class="simple">
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<li><p>Lab Wednesday: Introduction to software and repetition of Python Programming</p></li>
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<li><p>Lecture Thursday: Introduction to the course, what is Machine Learning and introduction to Linear Regression.</p></li>
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<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>
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||
<li><p>Lecture Friday: Basics of Linear Regression</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:</p>
|
||
<ul>
|
||
<li><p>Refresh linear algebra, GBC chapters 1 and 2.</p></li>
|
||
<li><p>CMB sections 1.1 and 3.1.</p></li>
|
||
<li><p>HTF chapters 2 and 3.</p></li>
|
||
<li><p>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>
|
||
</li>
|
||
</ul>
|
||
</div>
|
||
<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: 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:</p>
|
||
<ul>
|
||
<li><p>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>HTF chapter 3. GBC chapters 1 and and sections 3.1-3.11 and 5.1</p></li>
|
||
<li><p>CMB sections 1.1 and 3.1</p></li>
|
||
</ul>
|
||
</li>
|
||
</ul>
|
||
</div>
|
||
<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>Reading recommendations:</p>
|
||
<ul>
|
||
<li><p>Lectures on Regression 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>.</p></li>
|
||
<li><p>Bishop 1.1, 1.2, 2.1, 2.2, 2.3 and 3.1</p></li>
|
||
<li><p>Hastie et al chapter 3</p></li>
|
||
</ul>
|
||
</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: Work on Project 1</p></li>
|
||
<li><p>Lecture Thursday: Resampling methods, cross-validation and Bootstrap</p>
|
||
<ul>
|
||
<li><p>Thursday September 16: Summary of Ridge and Lasso with examples and start resampling techniques</p>
|
||
<ul>
|
||
<li><p>Video of Lecture, first part at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember16Firstpart.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember16Firstpart.mp4?vrtx=view-as-webpage</a>”</p></li>
|
||
<li><p>Video of Lecture, second part at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember16SecondPart.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember16SecondPart.mp4?vrtx=view-as-webpage</a></p></li>
|
||
</ul>
|
||
</li>
|
||
</ul>
|
||
</li>
|
||
<li><p>Lecture Friday: More on Resampling methods and summary of linear regression</p>
|
||
<ul>
|
||
<li><p>Video of Lecture at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember17.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember17.mp4?vrtx=view-as-webpage</a></p></li>
|
||
</ul>
|
||
</li>
|
||
<li><p>Reading recommendations:</p>
|
||
<ul>
|
||
<li><p>Lectures on Resampling methods 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></li>
|
||
<li><p>Bishop 1.3 (cross-validation) and 3.2 (bias-variance tradeoff)</p></li>
|
||
<li><p>Hastie et al Chapter 7, here we recommend 7.1-7.5 and 7.10 (cross-validation) and 7.11 (bootstrap)</p></li>
|
||
<li><p>Goodfellow et al discuss some of these topics in sections 5.2-5.5.</p></li>
|
||
</ul>
|
||
</li>
|
||
</ul>
|
||
</div>
|
||
<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: Work on Project 1</p></li>
|
||
<li><p>Lecture Thursday: Classification problems and Logistic Regression, from binary cases to several categories</p>
|
||
<ul>
|
||
<li><p>Video of Lecture at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureSeptember23.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureSeptember23.mp4?vrtx=view-as-webpage</a></p></li>
|
||
</ul>
|
||
</li>
|
||
<li><p>Lecture Friday: Logistic Regression and gradient optimization</p>
|
||
<ul>
|
||
<li><p>Video of Lecture at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember24.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember24.mp4?vrtx=view-as-webpage</a></p></li>
|
||
</ul>
|
||
</li>
|
||
<li><p>Reading recommendations:</p>
|
||
<ul>
|
||
<li><p>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></li>
|
||
<li><p>Bishop 4.1, 4.2 and 4.3. Not all the material is relevant or will be covered. Section 4.3 is the most relevant, but 4.1 and 4.2 give interesting background readings for logistic regression</p></li>
|
||
<li><p>Hastie et al 4.1, 4.2 and 4.3 on logistic regression</p></li>
|
||
<li><p>For a good discussion on gradient methods, see Goodfellow et al section 4.3-4.5 and chapter 8. We will come back to the latter chapter in our discussion of Neural networks as well.</p></li>
|
||
</ul>
|
||
</li>
|
||
</ul>
|
||
</div>
|
||
<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: Work on Project 1</p></li>
|
||
<li><p>Lecture Thursday: Gradient Optimization methods</p>
|
||
<ul>
|
||
<li><p>Video of Lecture at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember30.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember30.mp4?vrtx=view-as-webpage</a></p></li>
|
||
</ul>
|
||
</li>
|
||
<li><p>Lecture Friday: Gradient methods</p>
|
||
<ul>
|
||
<li><p>Video of Lecture at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober1.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober1.mp4?vrtx=view-as-webpage</a></p></li>
|
||
</ul>
|
||
</li>
|
||
<li><p>Reading recommendations:</p>
|
||
<ul>
|
||
<li><p>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></li>
|
||
<li><p>For a good discussion on gradient methods, see Goodfellow et al section 4.3-4.5 and chapter 8. We will come back to the latter chapter in our discussion of Neural networks as well.</p></li>
|
||
</ul>
|
||
</li>
|
||
</ul>
|
||
</div>
|
||
<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: Wrap up project 1</p></li>
|
||
<li><p>Lecture Thursday: Stochastic gradient descent, automatic differentiation and start discussion of feed-forward Neural Network code for regression and classification</p>
|
||
<ul>
|
||
<li><p>Video of Lecture at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober7.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober7.mp4?vrtx=view-as-webpage</a></p></li>
|
||
</ul>
|
||
</li>
|
||
<li><p>Lecture Friday: Deep Learning and Neural Networks: the back propagation algorithm</p>
|
||
<ul>
|
||
<li><p>Video of Lecture at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober8.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober8.mp4?vrtx=view-as-webpage</a></p></li>
|
||
</ul>
|
||
</li>
|
||
<li><p>Reading recommendations:</p>
|
||
<ul>
|
||
<li><p>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></li>
|
||
<li><p>For neural networks we recommend Goodfellow et al chapters 6 and 7 and Bishop 5.1-5.4</p></li>
|
||
<li><p>For stochastic gradient descent we recommend Goodfellow et al chapter 8</p></li>
|
||
</ul>
|
||
</li>
|
||
</ul>
|
||
</div>
|
||
<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: Work on project 2</p></li>
|
||
<li><p>Lecture Thursday: Deep learning and Neural Networks, developing a code for Neural Networks</p>
|
||
<ul>
|
||
<li><p>Video of Lecture at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober14.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober14.mp4?vrtx=view-as-webpage</a></p></li>
|
||
</ul>
|
||
</li>
|
||
<li><p>Lecture Friday: Tensorflow and the mathematics of neural network</p>
|
||
<ul>
|
||
<li><p>Video of Lecture at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureOctober15.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureOctober15.mp4?vrtx=view-as-webpage</a></p></li>
|
||
</ul>
|
||
</li>
|
||
<li><p>Reading recommendations:</p>
|
||
<ul>
|
||
<li><p>See lecture notes for week 41 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>For neural networks we recommend Goodfellow et al chapters 6 and 7. For CNNs, see Goodfellow et al chapter 9. chapter 11 and 12 on practicalities and applications</p></li>
|
||
</ul>
|
||
</li>
|
||
</ul>
|
||
</div>
|
||
<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: Work on project 2</p></li>
|
||
<li><p>Lecture Thursday: Solving differential equations with neural networks and start Convolutional Neural Networks and classification problems</p>
|
||
<ul>
|
||
<li><p>Video of Lecture at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober21.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober21.mp4?vrtx=view-as-webpage</a></p></li>
|
||
</ul>
|
||
</li>
|
||
<li><p>Lecture Friday: Convolutional Neural Networks and classification problems</p>
|
||
<ul>
|
||
<li><p>Video of Lecture at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureOctober22.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureOctober22.mp4?vrtx=view-as-webpage</a></p></li>
|
||
</ul>
|
||
</li>
|
||
<li><p>Reading recommendations:</p>
|
||
<ul>
|
||
<li><p>See lecture notes for week 42 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>For neural networks we recommend Goodfellow et al chapters 6 and 7. For CNNs, see Goodfellow et al chapter 9. See also chapter 11 and 12 on practicalities and applications</p></li>
|
||
</ul>
|
||
</li>
|
||
</ul>
|
||
</div>
|
||
<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: Work on project 2</p></li>
|
||
<li><p>Lecture Thursday: Recurrent Neural Networks</p></li>
|
||
<li><p>Lecture Friday: Recurrent Neural Networks and principal component analysis (PCA)</p></li>
|
||
<li><p>Reading recommendations:</p>
|
||
<ul>
|
||
<li><p>See lecture notes for week 43 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>For RNNs, see Goodfellow et al chapter 10 and discussions in chapter 11 and 12 on practicalities and applications</p></li>
|
||
<li><p>For PCA see lecture notes (jupyter book) chapter 11 and also chapter 12 on clustering. Geron’s chapter 8 is also a good read.</p></li>
|
||
</ul>
|
||
</li>
|
||
</ul>
|
||
</div>
|
||
<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: Work on project 2</p></li>
|
||
<li><p>Lecture Thursday: Decision trees, classification and regression</p></li>
|
||
<li><p>Lecture Friday: Decision trees, basic algorithms</p></li>
|
||
<li><p>Reading recommendations:</p>
|
||
<ul>
|
||
<li><p>See lecture notes for week 44 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>Hastie et al sections 9.1 and 9.2</p></li>
|
||
</ul>
|
||
</li>
|
||
</ul>
|
||
</div>
|
||
<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: Work on project 2 and start project 3</p></li>
|
||
<li><p>Lecture Thursday: Ensemble methods, bagging and random forests</p></li>
|
||
<li><p>Lecture Friday: Boosting and gradient boosting</p></li>
|
||
<li><p>Reading recommendations:</p>
|
||
<ul>
|
||
<li><p>See lecture notes for week 45 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>Hastie et al chapter 10</p></li>
|
||
</ul>
|
||
</li>
|
||
</ul>
|
||
</div>
|
||
<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: Work on project 3</p></li>
|
||
<li><p>Lecture Thursday: Support Vector machines</p></li>
|
||
<li><p>Lecture Friday: Support Vector machines</p></li>
|
||
<li><p>Reading recommendations:</p>
|
||
<ul>
|
||
<li><p>See lecture notes for week 46 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>Hastie et al chapter 12</p></li>
|
||
</ul>
|
||
</li>
|
||
</ul>
|
||
</div>
|
||
<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: Work on project 3</p></li>
|
||
<li><p>Lecture Thursday: Unsupervised Learning, Principal Component Analysis (PCA)</p></li>
|
||
<li><p>Lecture Friday: Unsupervised Learning and PCA, k-means and Clustering</p></li>
|
||
<li><p>Reading recommendations:</p>
|
||
<ul>
|
||
<li><p>See lecture notes for week 47 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>
|
||
</li>
|
||
</ul>
|
||
</div>
|
||
<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: Work on project 3</p></li>
|
||
<li><p>Lecture Thursday: Unsupervised Learning and Clustering</p></li>
|
||
<li><p>Lecture Friday: Summary of course</p></li>
|
||
<li><p>Reading recommendations:</p>
|
||
<ul>
|
||
<li><p>See lecture notes for week 48 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>
|
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</ul>
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