From bd0b1c1fd6524719130c244705c8ccdb2ed2ba42 Mon Sep 17 00:00:00 2001 From: Morten Hjorth-Jensen Date: Tue, 14 Sep 2021 22:59:18 +0200 Subject: [PATCH] Update README.md --- README.md | 38 +++++++++++++++++++++++++++----------- 1 file changed, 27 insertions(+), 11 deletions(-) diff --git a/README.md b/README.md index ab41cf5e2..4f8334b95 100644 --- a/README.md +++ b/README.md @@ -231,30 +231,45 @@ For the reading assignments we use the following abbreviations: Recommended prereading: Chapters 1-2 (linear algebra) and chapter 3 (statistics) of Goodfellow et al. and Bishop chapter 1 and chapter 2. These chapters give a relevant background to the basic mathematical and statistical foundations of the course. Parts of these chapters will be covered during the lectures the first three weeks. + + ### Week 34 August 23-27 - Lab Wednesday: Introduction to software and repetition of Python Programming -- Lecture Thursday: Introduction to the course, what is Machine Learning and introduction to Linear Regression +- Lecture Thursday: Introduction to the course, what is Machine Learning and introduction to Linear Regression. +- Video of Lecture August 26, 2021 at https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureThursdayAugust26.mp4?vrtx=view-as-webpage - Lecture Friday: Basics of Linear Regression +- Video of Lecture August 27, 2021 at https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureThursdayAugust27.mp4?vrtx=view-as-webpage - 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 https://compphysics.github.io/MachineLearning/doc/web/course.html ### Week 35 August 30-September 3 -- Lab Wednesday: -- Lecture Thursday: Linear Regression, from ordinary linear regression to Ridge and Lasso regression, linear algebra analysis, examples and discussions of codes -- Lecture Friday: Linear Regression, Linear algebra and Ridge and Lasso Regression, linear algebra analysis, examples and discussions of codes +- 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 +- Video of lecture Thursday at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember2.mp4?vrtx=view-as-webpage". +- Friday: Analysis of Ridge and Lasso Regression and links with Singular Value Decomposition +- Video of lecture Friday at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember3.mp4?vrtx=view-as-webpage" - Reading recommendations: See lecture notes for week 35 at https://compphysics.github.io/MachineLearning/doc/web/course.html. HTF chapter 3. GBC chapters 1 and and sections 3.1-3.11 and 5.1 and CMB sections 1.1 and 3.1 + ### Week 36 September 6-10 -- Lab Wednesday: -- Lecture Thursday: Ridge and Lasso regression and the SVD. Statistical interpretation of Linear Regression -- Lecture Friday: Further interpretations of Linear regression. -- Reading recommendations: See lecture notes for week 36 at https://compphysics.github.io/MachineLearning/doc/web/course.html. GBC sections 5.2-5.5, CMB section 3.2 - - Chapter +- Lab Wednesday: Exercises 1 and 2 from week 36 +- Lecture Thursday: Summary from last week on SVD, Statistics, probability theory and linear regression +- Video of Lecture https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember9.mp4?vrtx=view-as-webpage". +- Friday: Linear Regression and links with Statistics, Resampling methods and presentation of first project. +- Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureSeptember10.mp4?vrtx=view-as-webpage" + +- Recommended Reading: Lectures on Regression, Bishop 1.1, 1.2, 2.1, 2.2, 2.3 and 3.1, Hastie et al chapter 3 + ### Week 37 September 13-17 - Lab Wednesday: - Lecture Thursday: Resampling methods, cross-validation and Bootstrap - Lecture Friday: More on Resampling methods and summary of linear regression -- Reading recommendations: See lecture notes for week 37 at https://compphysics.github.io/MachineLearning/doc/web/course.html. - - Chapter +- Reading recommendations: +- Recommended Reading: + - Lectures on Resampling methods for week 37 at https://compphysics.github.io/MachineLearning/doc/web/course.html. + - Bishop 1.3 (cross-validation) and 3.2 (bias-variance tradeoff) + - Hastie et al Chapter 7, here we recommend 7.1-7.5 and 7.10 (cross-validation) and 7.11 (bootstrap). This chapter is better than Bishop's on these topics. Goodfellow et al discuss some of these topics in sections 5.2-5.5. + + ### Week 38 September 20-24 - Lab Wednesday: - Lecture Thursday: Classification problems and Logistic Regression, from binary cases to several categories @@ -324,3 +339,4 @@ Recommended prereading: Chapters 1-2 (linear algebra) and chapter 3 (statistics) +