From 512d5e46305870586770b87f1ae914e91df5dcfb Mon Sep 17 00:00:00 2001 From: Morten Hjorth-Jensen Date: Sun, 28 Aug 2022 22:16:46 +0200 Subject: [PATCH] Update schedule.md --- doc/LectureNotes/schedule.md | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/doc/LectureNotes/schedule.md b/doc/LectureNotes/schedule.md index 11030f65c..2e9a2d89f 100644 --- a/doc/LectureNotes/schedule.md +++ b/doc/LectureNotes/schedule.md @@ -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: