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Morten Hjorth-Jensen
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@@ -36,23 +36,24 @@ For the reading assignments we use the following abbreviations:
- See lecture notes for week 34 at https://compphysics.github.io/MachineLearning/doc/web/course.html
### Week 35 August 29-September 2
- Lab Wednesday: Work on exercises 1-3 for week 35
- Thursday: Review of ordinary Least Squares with applications and discussion of Ridge Regression and Singular Value Decomposition
- Lab Wednesday: Work on exercises 1-5 for week 35
- Thursday: Review of ordinary Least Squares with applications, reminder on statistics and start discussion of Ridge Regression and Singular Value Decomposition
- Video of lecture Thursday at
- Friday: Analysis of Ridge and Lasso Regression and links with Singular Value Decomposition
- Friday: Discussion of Ridge and Lasso Regression and links with Singular Value Decomposition
- Video of lecture Friday at
- Reading recommendations:
- See lecture notes for week 35 at https://compphysics.github.io/MachineLearning/doc/web/course.html.
- For a review on statistics see jupyter-book https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/statistics.html, the most relevant parts are covered by sections 1.1.1-1.1.5
- HTF chapter 3. GBC chapters 1 and and sections 3.1-3.11 and 5.1
- CMB sections 1.1 and 3.1
- A good review on statistics is given by Murphy's text, chapter 2, see https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/MachineLearningMurphy.pdf
### Week 36 September 5-9
- Lab Wednesday: Exercises 1 and 2 from week 36
- Lecture Thursday: Summary from last week on SVD, Statistics, probability theory and linear regression
- Lecture Thursday: Summary from last week on SVD, more on Statistics, probability theory and linear regression
- Video of Lecture
- Friday: Linear Regression and links with Statistics, Resampling methods and presentation of first project.
- Friday: Linear Regression and more links with Statistics, Resampling methods and presentation of first project.
- Video of Lecture
- Reading recommendations: