From 55a4e22aeb3c5b73c1830a9cf0638dec7ce0b6a4 Mon Sep 17 00:00:00 2001 From: Morten Hjorth-Jensen Date: Wed, 31 May 2023 13:18:39 +0200 Subject: [PATCH] Update week40.do.txt --- doc/src/week40/week40.do.txt | 8 +++----- 1 file changed, 3 insertions(+), 5 deletions(-) diff --git a/doc/src/week40/week40.do.txt b/doc/src/week40/week40.do.txt index ec041be4c..22899c0e5 100644 --- a/doc/src/week40/week40.do.txt +++ b/doc/src/week40/week40.do.txt @@ -1,15 +1,13 @@ TITLE: Week 40: Neural networks AUTHOR: Morten Hjorth-Jensen {copyright, 1999-present|CC BY-NC} at Department of Physics, University of Oslo, Norway & Department of Physics and Astronomy and Facility for Rare Ion Beams, Michigan State University, USA -DATE: today +DATE: Week 40, 2023 !split ===== Plan for week 40 ===== -* Thursday: Repetion and summary of Stochastic Gradient descent with examples and automatic differentiation and begin Neural Networks. - * "Video of lecture":"https://youtu.be/sCHiGSoG2lE" -* Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model. Presentation of project 2. - * "Video of lecture":"https://youtu.be/hDTtA7PRRfI" +* Repetion and summary of Stochastic Gradient descent with examples and automatic differentiation and begin Neural Networks. +* Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model. Presentation of project 2. Reading suggestions for both days: "Aurelien Geron's chapter 10":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf" and Hastie et al chapter 11. For Stochastic Gradient Descent, we recommend chapter 4 of Geron's text.