From 63ec4370a1529f6ce282253f8d48f96182432183 Mon Sep 17 00:00:00 2001 From: Morten Hjorth-Jensen Date: Sat, 11 Sep 2021 23:19:26 +0200 Subject: [PATCH] Update README.md --- README.md | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index 65729324f..ab41cf5e2 100644 --- a/README.md +++ b/README.md @@ -235,37 +235,37 @@ Recommended prereading: Chapters 1-2 (linear algebra) and chapter 3 (statistics) - 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 Friday: Basics of Linear Regression -- 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 https://compphysics.github.io/MachineLearning/doc/web/course.html +- 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 -- Reading recommendations: See lecture notes for week 36 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 +- 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: Statistical interpretation of Linear Regression -- Lecture Friday: Bias-Variance tradeoff -- Reading recommendations: See lecture notes for week 37 at https://compphysics.github.io/MachineLearning/doc/web/course.html. GBC sections 5.2-5.5, CMB section 3.2 +- 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 ### 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 38 at https://compphysics.github.io/MachineLearning/doc/web/course.html. +- Reading recommendations: See lecture notes for week 37 at https://compphysics.github.io/MachineLearning/doc/web/course.html. - Chapter ### Week 38 September 20-24 - Lab Wednesday: - Lecture Thursday: Classification problems and Logistic Regression, from binary cases to several categories - Lecture Friday: Logistic Regression and gradient optimization -- Reading recommendations: See lecture notes for week 39 at https://compphysics.github.io/MachineLearning/doc/web/course.html. +- Reading recommendations: See lecture notes for week 38 at https://compphysics.github.io/MachineLearning/doc/web/course.html. - Chapter ### Week 39 September 27- October 1 - Lab Wednesday: - Lecture Thursday: Gradient Optimization methods - Lecture Friday: Deep Learning and Neural Networks -- Reading recommendations: See lecture notes for week 40 at https://compphysics.github.io/MachineLearning/doc/web/course.html. +- Reading recommendations: See lecture notes for week 39 at https://compphysics.github.io/MachineLearning/doc/web/course.html. - Chapter ### Week 40 October 4-8 - Lab Wednesday: