From c249f07d661cbfcb46e0c2327be1e6e0e67d933c Mon Sep 17 00:00:00 2001
From: mhjensen <morten.hjorth-jensen@fys.uio.no>
Date: Sun, 27 Sep 2020 21:56:50 +0200
Subject: [PATCH] setting up week 40

---
 doc/pub/week40/ipynb/ipynb-week40-src.tar.gz | Bin 196 -> 190 bytes
 doc/pub/week40/ipynb/week40.ipynb            |  17 ++++++++++++++--
 doc/src/week40/week40.do.txt                 |  20 +++++++++++++++++++
 3 files changed, 35 insertions(+), 2 deletions(-)

diff --git a/doc/pub/week40/ipynb/ipynb-week40-src.tar.gz b/doc/pub/week40/ipynb/ipynb-week40-src.tar.gz
index 37680988076948517819774d4f58275923748ec6..2ce9043697432db94e8eaca25ea03d791cc275d7 100644
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diff --git a/doc/pub/week40/ipynb/week40.ipynb b/doc/pub/week40/ipynb/week40.ipynb
index 5783e637b..2cedc09b2 100644
--- a/doc/pub/week40/ipynb/week40.ipynb
+++ b/doc/pub/week40/ipynb/week40.ipynb
@@ -10,13 +10,26 @@
     "<!-- Author: -->  \n",
     "**Morten Hjorth-Jensen**, Department of Physics, University of Oslo and Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University\n",
     "\n",
-    "Date: **Sep 16, 2020**\n",
+    "Date: **Sep 27, 2020**\n",
     "\n",
     "Copyright 1999-2020, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license\n",
     "\n",
     "\n",
     "\n",
     "\n",
+    "## Plan for week 40\n",
+    "\n",
+    "* Thursday: Stochastic Gradient descent with examples and automatic differeantion and begin Neural Networks \n",
+    "\n",
+    "* Friday: Neural Networks, setting up the basic steps\n",
+    "\n",
+    "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.\n",
+    "\n",
+    "## Overview video for week 40\n",
+    "\n",
+    "[Overview Video, fro Stochastic Gradient methods to Neural Networks](https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/OverarchingAimsWeek40.mp4?vrtx=view-as-webpage)\n",
+    "\n",
+    "\n",
     "\n",
     "## Neural networks\n",
     "\n",
@@ -3312,5 +3325,5 @@
  ],
  "metadata": {},
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }
diff --git a/doc/src/week40/week40.do.txt b/doc/src/week40/week40.do.txt
index 75e2e36ef..28ea02505 100644
--- a/doc/src/week40/week40.do.txt
+++ b/doc/src/week40/week40.do.txt
@@ -3,6 +3,21 @@ AUTHOR: Morten Hjorth-Jensen {copyright, 1999-present|CC BY-NC} at Department of
 DATE: today
 
 
+!split
+===== Plan for week 40 =====
+
+* Thursday: Stochastic Gradient descent with examples and automatic differeantion and begin Neural Networks 
+* Friday: Neural Networks, setting up the basic steps
+
+
+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.
+
+!split
+===== Overview video for week 40 =====
+
+"Overview Video, fro Stochastic Gradient methods to Neural Networks":"https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/OverarchingAimsWeek40.mp4?vrtx=view-as-webpage"
+
+
 
 !split
 ===== Neural networks =====
@@ -2452,3 +2467,8 @@ Here we list some of the important limitations of supervised neural network base
 Some of these remarks are particular to DNNs, others are shared by all supervised learning methods. This motivates the use of unsupervised methods which in part circumvent these problems.
 
 
+
+
+
+
+