diff --git a/doc/pub/week40/html/._week40-bs001.html b/doc/pub/week40/html/._week40-bs001.html index 89fa72667..90d1cbdbb 100644 --- a/doc/pub/week40/html/._week40-bs001.html +++ b/doc/pub/week40/html/._week40-bs001.html @@ -257,10 +257,11 @@ MathJax.Hub.Config({
    -
  1. Stochastic Gradient descent with examples and automatic differentiation
    2. -
  2. If we get time, we start with the basics of Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model
    3. -
  3. Video of lecture
    4. -
  4. Whiteboard notes at https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember30.pdf
    5. +
  5. Logistic regression and gradient descent, examples on how to code
    6. +
  6. Automatic differentiation and gradient descent, examples using Logistic regression
    7. +
  7. Start with the basics of Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model + +
diff --git a/doc/pub/week40/html/._week40-bs002.html b/doc/pub/week40/html/._week40-bs002.html index c23ffe247..fab58dab4 100644 --- a/doc/pub/week40/html/._week40-bs002.html +++ b/doc/pub/week40/html/._week40-bs002.html @@ -259,9 +259,9 @@ MathJax.Hub.Config({
  1. The lecture notes for week 40 (these notes)
  2. For a good discussion on gradient methods, we would like to recommend Goodfellow et al section 4.3-4.5 and sections 8.3-8.6. We will come back to the latter chapter in our discussion of Neural networks as well.
    3. -
  3. For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al chapter 2 (contains also material about gradient descent) and chapter 11 (we will use this next week)
    4. -
  4. Video on gradient descent at https://www.youtube.com/watch?v=sDv4f4s2SB8
    5. -
  5. Video on stochastic gradient descent at https://www.youtube.com/watch?v=vMh0zPT0tLI
    6. +
  6. For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al chapter 2 (contains also material about gradient descent) and chapter 11 (we will use this next week) +
    7. +
  7. Video on automatic differentiation at https://www.youtube.com/watch?v=wG_nF1awSSY
  8. Neural Networks demystified at https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs
  9. Building Neural Networks from scratch at URL:https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3&ab_channel=sentdex"
diff --git a/doc/pub/week40/html/week40-reveal.html b/doc/pub/week40/html/week40-reveal.html index acc77e203..dd25e28ea 100644 --- a/doc/pub/week40/html/week40-reveal.html +++ b/doc/pub/week40/html/week40-reveal.html @@ -197,10 +197,11 @@ MathJax.Hub.Config({

    -

  1. Stochastic Gradient descent with examples and automatic differentiation
    2. -

  2. If we get time, we start with the basics of Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model
    3. -

  3. Video of lecture
    4. -

  4. Whiteboard notes at https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember30.pdf
    5. +

  5. Logistic regression and gradient descent, examples on how to code
    6. +

  6. Automatic differentiation and gradient descent, examples using Logistic regression
    7. +

  7. Start with the basics of Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model + +
@@ -216,11 +217,10 @@ MathJax.Hub.Config({

  • For a good discussion on gradient methods, we would like to recommend Goodfellow et al section 4.3-4.5 and sections 8.3-8.6. We will come back to the latter chapter in our discussion of Neural networks as well.
    • -

  • For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al chapter 2 (contains also material about gradient descent) and chapter 11 (we will use this next week)
    • +

  • For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al chapter 2 (contains also material about gradient descent) and chapter 11 (we will use this next week) +
    • -

  • Video on gradient descent at https://www.youtube.com/watch?v=sDv4f4s2SB8
    • - -

  • Video on stochastic gradient descent at https://www.youtube.com/watch?v=vMh0zPT0tLI
    • +

  • Video on automatic differentiation at https://www.youtube.com/watch?v=wG_nF1awSSY

  • Neural Networks demystified at https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs
    • diff --git a/doc/pub/week40/html/week40-solarized.html b/doc/pub/week40/html/week40-solarized.html index bee8bc88f..70a34618f 100644 --- a/doc/pub/week40/html/week40-solarized.html +++ b/doc/pub/week40/html/week40-solarized.html @@ -232,10 +232,11 @@ MathJax.Hub.Config({

      -
    1. Stochastic Gradient descent with examples and automatic differentiation
      2. -
    2. If we get time, we start with the basics of Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model
      3. -
    3. Video of lecture
      4. -
    4. Whiteboard notes at https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember30.pdf
      5. +
    5. Logistic regression and gradient descent, examples on how to code
      6. +
    6. Automatic differentiation and gradient descent, examples using Logistic regression
      7. +
    7. Start with the basics of Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model + +
    @@ -248,9 +249,9 @@ MathJax.Hub.Config({
    1. The lecture notes for week 40 (these notes)
    2. For a good discussion on gradient methods, we would like to recommend Goodfellow et al section 4.3-4.5 and sections 8.3-8.6. We will come back to the latter chapter in our discussion of Neural networks as well.
      3. -
    3. For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al chapter 2 (contains also material about gradient descent) and chapter 11 (we will use this next week)
      4. -
    4. Video on gradient descent at https://www.youtube.com/watch?v=sDv4f4s2SB8
      5. -
    5. Video on stochastic gradient descent at https://www.youtube.com/watch?v=vMh0zPT0tLI
      6. +
    6. For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al chapter 2 (contains also material about gradient descent) and chapter 11 (we will use this next week) +
      7. +
    7. Video on automatic differentiation at https://www.youtube.com/watch?v=wG_nF1awSSY
    8. Neural Networks demystified at https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs
    9. Building Neural Networks from scratch at URL:https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3&ab_channel=sentdex"
    diff --git a/doc/pub/week40/html/week40.html b/doc/pub/week40/html/week40.html index bf39f9635..e46a9e55d 100644 --- a/doc/pub/week40/html/week40.html +++ b/doc/pub/week40/html/week40.html @@ -309,10 +309,11 @@ MathJax.Hub.Config({

      -
    1. Stochastic Gradient descent with examples and automatic differentiation
      2. -
    2. If we get time, we start with the basics of Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model
      3. -
    3. Video of lecture
      4. -
    4. Whiteboard notes at https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember30.pdf
      5. +
    5. Logistic regression and gradient descent, examples on how to code
      6. +
    6. Automatic differentiation and gradient descent, examples using Logistic regression
      7. +
    7. Start with the basics of Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model + +
    @@ -325,9 +326,9 @@ MathJax.Hub.Config({
    1. The lecture notes for week 40 (these notes)
    2. For a good discussion on gradient methods, we would like to recommend Goodfellow et al section 4.3-4.5 and sections 8.3-8.6. We will come back to the latter chapter in our discussion of Neural networks as well.
      3. -
    3. For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al chapter 2 (contains also material about gradient descent) and chapter 11 (we will use this next week)
      4. -
    4. Video on gradient descent at https://www.youtube.com/watch?v=sDv4f4s2SB8
      5. -
    5. Video on stochastic gradient descent at https://www.youtube.com/watch?v=vMh0zPT0tLI
      6. +
    6. For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al chapter 2 (contains also material about gradient descent) and chapter 11 (we will use this next week) +
      7. +
    7. Video on automatic differentiation at https://www.youtube.com/watch?v=wG_nF1awSSY
    8. Neural Networks demystified at https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs
    9. Building Neural Networks from scratch at URL:https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3&ab_channel=sentdex"
    diff --git a/doc/pub/week40/ipynb/ipynb-week40-src.tar.gz b/doc/pub/week40/ipynb/ipynb-week40-src.tar.gz index 67627a2f7..3dd13da71 100644 Binary files a/doc/pub/week40/ipynb/ipynb-week40-src.tar.gz and b/doc/pub/week40/ipynb/ipynb-week40-src.tar.gz differ diff --git a/doc/pub/week40/ipynb/week40.ipynb b/doc/pub/week40/ipynb/week40.ipynb index 9bd4253a2..9c9e453ac 100644 --- a/doc/pub/week40/ipynb/week40.ipynb +++ b/doc/pub/week40/ipynb/week40.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "1d679faf", + "id": "2f68fa23", "metadata": { "editable": true }, @@ -14,7 +14,7 @@ }, { "cell_type": "markdown", - "id": "1d86ca93", + "id": "853c19c5", "metadata": { "editable": true }, @@ -27,24 +27,24 @@ }, { "cell_type": "markdown", - "id": "e69a8d43", + "id": "4380de79", "metadata": { "editable": true }, "source": [ "## Lecture Monday September 30, 2024\n", - "1. Stochastic Gradient descent with examples and automatic differentiation\n", + "1. Logistic regression and gradient descent, examples on how to code\n", "\n", - "2. If we get time, we start with the basics of Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model\n", + "2. Automatic differentiation and gradient descent, examples using Logistic regression\n", "\n", - "3. [Video of lecture](https://youtu.be/jdJoOrCIdII)\n", - "\n", - "4. Whiteboard notes at " + "3. Start with the basics of Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model\n", + "\n", + "" ] }, { "cell_type": "markdown", - "id": "f48ef548", + "id": "68503778", "metadata": { "editable": true }, @@ -57,19 +57,18 @@ "2. For a good discussion on gradient methods, we would like to recommend Goodfellow et al section 4.3-4.5 and sections 8.3-8.6. We will come back to the latter chapter in our discussion of Neural networks as well.\n", "\n", "3. For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al chapter 2 (contains also material about gradient descent) and chapter 11 (we will use this next week)\n", + "\n", "\n", - "4. Video on gradient descent at \n", + "4. Video on automatic differentiation at \n", "\n", - "5. Video on stochastic gradient descent at \n", + "5. Neural Networks demystified at \n", "\n", - "6. Neural Networks demystified at \n", - "\n", - "7. Building Neural Networks from scratch at URL:https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3&ab_channel=sentdex\"" + "6. Building Neural Networks from scratch at URL:https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3&ab_channel=sentdex\"" ] }, { "cell_type": "markdown", - "id": "cfccf861", + "id": "0cde2d72", "metadata": { "editable": true }, @@ -88,7 +87,7 @@ }, { "cell_type": "markdown", - "id": "0d567b76", + "id": "b3867438", "metadata": { "editable": true }, @@ -126,7 +125,7 @@ }, { "cell_type": "markdown", - "id": "29059bbb", + "id": "8c466881", "metadata": { "editable": true }, @@ -138,7 +137,7 @@ }, { "cell_type": "markdown", - "id": "000637ed", + "id": "4363c443", "metadata": { "editable": true }, @@ -148,7 +147,7 @@ }, { "cell_type": "markdown", - "id": "73499fad", + "id": "6a0081a9", "metadata": { "editable": true }, @@ -160,7 +159,7 @@ }, { "cell_type": "markdown", - "id": "a2c54b7e", + "id": "e8dc4001", "metadata": { "editable": true }, @@ -171,7 +170,7 @@ { "cell_type": "code", "execution_count": 1, - "id": "45af1608", + "id": "905b3b58", "metadata": { "collapsed": false, "editable": true @@ -218,7 +217,7 @@ }, { "cell_type": "markdown", - "id": "4fa94bf0", + "id": "5acaa3d4", "metadata": { "editable": true }, @@ -235,7 +234,7 @@ { "cell_type": "code", "execution_count": 2, - "id": "fa3182e1", + "id": "88bc12fe", "metadata": { "collapsed": false, "editable": true @@ -263,7 +262,7 @@ }, { "cell_type": "markdown", - "id": "3b52d711", + "id": "0aac1edd", "metadata": { "editable": true }, @@ -278,7 +277,7 @@ { "cell_type": "code", "execution_count": 3, - "id": "f9f046ce", + "id": "0d54b347", "metadata": { "collapsed": false, "editable": true @@ -322,7 +321,7 @@ }, { "cell_type": "markdown", - "id": "f8014a36", + "id": "d244af73", "metadata": { "editable": true }, @@ -332,7 +331,7 @@ }, { "cell_type": "markdown", - "id": "12725415", + "id": "39a3a271", "metadata": { "editable": true }, @@ -343,7 +342,7 @@ { "cell_type": "code", "execution_count": 4, - "id": "628f6795", + "id": "ad571062", "metadata": { "collapsed": false, "editable": true @@ -371,7 +370,7 @@ }, { "cell_type": "markdown", - "id": "efce6ad6", + "id": "7164fa95", "metadata": { "editable": true }, @@ -386,7 +385,7 @@ }, { "cell_type": "markdown", - "id": "4eb6cad9", + "id": "e441d2f7", "metadata": { "editable": true }, @@ -397,7 +396,7 @@ { "cell_type": "code", "execution_count": 5, - "id": "1d192367", + "id": "48579d0f", "metadata": { "collapsed": false, "editable": true @@ -425,7 +424,7 @@ }, { "cell_type": "markdown", - "id": "9aec62ef", + "id": "c322cbb0", "metadata": { "editable": true }, @@ -436,7 +435,7 @@ { "cell_type": "code", "execution_count": 6, - "id": "fec7a34e", + "id": "5bca0c19", "metadata": { "collapsed": false, "editable": true @@ -461,7 +460,7 @@ }, { "cell_type": "markdown", - "id": "d18fb67b", + "id": "95eb2b82", "metadata": { "editable": true }, @@ -472,7 +471,7 @@ { "cell_type": "code", "execution_count": 7, - "id": "54456259", + "id": "cbc87ed8", "metadata": { "collapsed": false, "editable": true @@ -508,7 +507,7 @@ { "cell_type": "code", "execution_count": 8, - "id": "6cb94658", + "id": "775932e2", "metadata": { "collapsed": false, "editable": true @@ -528,7 +527,7 @@ }, { "cell_type": "markdown", - "id": "d0e990b8", + "id": "5ac5ed9f", "metadata": { "editable": true }, @@ -539,7 +538,7 @@ { "cell_type": "code", "execution_count": 9, - "id": "ba57a27f", + "id": "a96515cd", "metadata": { "collapsed": false, "editable": true @@ -577,7 +576,7 @@ }, { "cell_type": "markdown", - "id": "23ed8fa4", + "id": "f864721b", "metadata": { "editable": true }, @@ -587,7 +586,7 @@ }, { "cell_type": "markdown", - "id": "56614917", + "id": "b8adab19", "metadata": { "editable": true }, @@ -602,7 +601,7 @@ { "cell_type": "code", "execution_count": 10, - "id": "5d6f4267", + "id": "f1e5b913", "metadata": { "collapsed": false, "editable": true @@ -662,7 +661,7 @@ }, { "cell_type": "markdown", - "id": "3317708a", + "id": "be1120fb", "metadata": { "editable": true }, @@ -673,7 +672,7 @@ { "cell_type": "code", "execution_count": 11, - "id": "b91eabff", + "id": "6c4a18b0", "metadata": { "collapsed": false, "editable": true @@ -737,7 +736,7 @@ }, { "cell_type": "markdown", - "id": "34a4da26", + "id": "b7c49b65", "metadata": { "editable": true }, @@ -749,7 +748,7 @@ { "cell_type": "code", "execution_count": 12, - "id": "ec7a759d", + "id": "74a00f6c", "metadata": { "collapsed": false, "editable": true @@ -833,7 +832,7 @@ }, { "cell_type": "markdown", - "id": "605be519", + "id": "90aca0ea", "metadata": { "editable": true }, @@ -844,7 +843,7 @@ { "cell_type": "code", "execution_count": 13, - "id": "8fc8795f", + "id": "1a48d186", "metadata": { "collapsed": false, "editable": true @@ -922,7 +921,7 @@ }, { "cell_type": "markdown", - "id": "3d4f6a0c", + "id": "414a327c", "metadata": { "editable": true }, @@ -933,7 +932,7 @@ { "cell_type": "code", "execution_count": 14, - "id": "d3bcc017", + "id": "b3cafce4", "metadata": { "collapsed": false, "editable": true @@ -992,7 +991,7 @@ }, { "cell_type": "markdown", - "id": "3536497d", + "id": "f8111f5b", "metadata": { "editable": true }, @@ -1002,7 +1001,7 @@ }, { "cell_type": "markdown", - "id": "2c8e701a", + "id": "e617c9e2", "metadata": { "editable": true }, @@ -1013,7 +1012,7 @@ { "cell_type": "code", "execution_count": 15, - "id": "57e7949a", + "id": "b532c75d", "metadata": { "collapsed": false, "editable": true @@ -1078,7 +1077,7 @@ }, { "cell_type": "markdown", - "id": "5910fed9", + "id": "30f60ba8", "metadata": { "editable": true }, @@ -1089,7 +1088,7 @@ { "cell_type": "code", "execution_count": 16, - "id": "4765630f", + "id": "ad750750", "metadata": { "collapsed": false, "editable": true @@ -1159,7 +1158,7 @@ }, { "cell_type": "markdown", - "id": "28731b27", + "id": "3a8f5219", "metadata": { "editable": true }, @@ -1170,7 +1169,7 @@ { "cell_type": "code", "execution_count": 17, - "id": "814be546", + "id": "59e87eb2", "metadata": { "collapsed": false, "editable": true @@ -1214,7 +1213,7 @@ }, { "cell_type": "markdown", - "id": "96ab7076", + "id": "8a90cdda", "metadata": { "editable": true }, @@ -1230,7 +1229,7 @@ }, { "cell_type": "markdown", - "id": "1f44fe55", + "id": "6ac18de3", "metadata": { "editable": true }, @@ -1241,7 +1240,7 @@ { "cell_type": "code", "execution_count": 18, - "id": "96d73091", + "id": "c65f20ac", "metadata": { "collapsed": false, "editable": true @@ -1258,7 +1257,7 @@ }, { "cell_type": "markdown", - "id": "51a09d4c", + "id": "d62bd197", "metadata": { "editable": true }, @@ -1269,7 +1268,7 @@ { "cell_type": "code", "execution_count": 19, - "id": "4914cdc2", + "id": "a40b3c24", "metadata": { "collapsed": false, "editable": true @@ -1314,7 +1313,7 @@ }, { "cell_type": "markdown", - "id": "6d209f7a", + "id": "f15e6af8", "metadata": { "editable": true }, @@ -1325,7 +1324,7 @@ { "cell_type": "code", "execution_count": 20, - "id": "77a1efbb", + "id": "6b629f3c", "metadata": { "collapsed": false, "editable": true @@ -1356,7 +1355,7 @@ }, { "cell_type": "markdown", - "id": "7bb9838b", + "id": "88f9e790", "metadata": { "editable": true }, @@ -1374,7 +1373,7 @@ }, { "cell_type": "markdown", - "id": "dd1332c8", + "id": "a1b9f91b", "metadata": { "editable": true }, @@ -1398,7 +1397,7 @@ }, { "cell_type": "markdown", - "id": "52a4d54b", + "id": "4a0fbd50", "metadata": { "editable": true }, @@ -1416,7 +1415,7 @@ }, { "cell_type": "markdown", - "id": "30b9994e", + "id": "3c98fd56", "metadata": { "editable": true }, @@ -1456,7 +1455,7 @@ }, { "cell_type": "markdown", - "id": "7513bdfb", + "id": "63b3bfed", "metadata": { "editable": true }, @@ -1485,7 +1484,7 @@ }, { "cell_type": "markdown", - "id": "bc80a3c0", + "id": "32b8beae", "metadata": { "editable": true }, @@ -1506,7 +1505,7 @@ }, { "cell_type": "markdown", - "id": "de15fe45", + "id": "26cc6f76", "metadata": { "editable": true }, @@ -1535,7 +1534,7 @@ }, { "cell_type": "markdown", - "id": "c028ac51", + "id": "1eb051bf", "metadata": { "editable": true }, @@ -1556,7 +1555,7 @@ }, { "cell_type": "markdown", - "id": "e476ba1f", + "id": "10f0ee19", "metadata": { "editable": true }, @@ -1577,7 +1576,7 @@ }, { "cell_type": "markdown", - "id": "ec7b958f", + "id": "d8d02f37", "metadata": { "editable": true }, @@ -1594,7 +1593,7 @@ }, { "cell_type": "markdown", - "id": "6b829eda", + "id": "cb76799a", "metadata": { "editable": true }, @@ -1615,7 +1614,7 @@ }, { "cell_type": "markdown", - "id": "14e38937", + "id": "154bff65", "metadata": { "editable": true }, @@ -1631,7 +1630,7 @@ }, { "cell_type": "markdown", - "id": "793fa0f6", + "id": "a4c801fb", "metadata": { "editable": true }, @@ -1648,7 +1647,7 @@ { "cell_type": "code", "execution_count": 21, - "id": "31c32fb1", + "id": "03ffff4a", "metadata": { "collapsed": false, "editable": true @@ -1689,7 +1688,7 @@ }, { "cell_type": "markdown", - "id": "0652d853", + "id": "11e1cee6", "metadata": { "editable": true }, @@ -1699,7 +1698,7 @@ }, { "cell_type": "markdown", - "id": "49f95bfa", + "id": "9e1430f7", "metadata": { "editable": true }, @@ -1710,7 +1709,7 @@ { "cell_type": "code", "execution_count": 22, - "id": "6ed55d22", + "id": "46a0c0f8", "metadata": { "collapsed": false, "editable": true @@ -1770,7 +1769,7 @@ }, { "cell_type": "markdown", - "id": "593bafc0", + "id": "fa182dca", "metadata": { "editable": true }, @@ -1780,7 +1779,7 @@ }, { "cell_type": "markdown", - "id": "a772ee66", + "id": "6c9bf9ec", "metadata": { "editable": true }, @@ -1791,7 +1790,7 @@ { "cell_type": "code", "execution_count": 23, - "id": "3131b91b", + "id": "8d453e68", "metadata": { "collapsed": false, "editable": true @@ -1811,7 +1810,7 @@ }, { "cell_type": "markdown", - "id": "f3072a05", + "id": "b3ad93a5", "metadata": { "editable": true }, @@ -1823,7 +1822,7 @@ }, { "cell_type": "markdown", - "id": "2501b704", + "id": "f0142ec9", "metadata": { "editable": true }, @@ -1835,7 +1834,7 @@ }, { "cell_type": "markdown", - "id": "0c9284d8", + "id": "9e683ae4", "metadata": { "editable": true }, @@ -1850,7 +1849,7 @@ }, { "cell_type": "markdown", - "id": "d9a0a94c", + "id": "f4fc251d", "metadata": { "editable": true }, @@ -1862,7 +1861,7 @@ }, { "cell_type": "markdown", - "id": "df8b7427", + "id": "5664e950", "metadata": { "editable": true }, @@ -1879,7 +1878,7 @@ }, { "cell_type": "markdown", - "id": "f0db3236", + "id": "263253de", "metadata": { "editable": true }, @@ -1894,7 +1893,7 @@ }, { "cell_type": "markdown", - "id": "ba90159e", + "id": "90eb86da", "metadata": { "editable": true }, @@ -1912,7 +1911,7 @@ }, { "cell_type": "markdown", - "id": "00e8a63c", + "id": "5a9ce0a9", "metadata": { "editable": true }, @@ -1924,7 +1923,7 @@ }, { "cell_type": "markdown", - "id": "99259806", + "id": "8d07a0e7", "metadata": { "editable": true }, @@ -1942,7 +1941,7 @@ }, { "cell_type": "markdown", - "id": "ca3efcd2", + "id": "711a41d1", "metadata": { "editable": true }, @@ -1955,7 +1954,7 @@ }, { "cell_type": "markdown", - "id": "bc1752b7", + "id": "951e138b", "metadata": { "editable": true }, @@ -1967,7 +1966,7 @@ }, { "cell_type": "markdown", - "id": "2f38f49c", + "id": "1d6ac66a", "metadata": { "editable": true }, @@ -1985,7 +1984,7 @@ }, { "cell_type": "markdown", - "id": "17273cad", + "id": "86980b1f", "metadata": { "editable": true }, @@ -2003,7 +2002,7 @@ }, { "cell_type": "markdown", - "id": "292f1932", + "id": "3e716ee6", "metadata": { "editable": true }, @@ -2013,7 +2012,7 @@ }, { "cell_type": "markdown", - "id": "55e276cb", + "id": "2a995bfc", "metadata": { "editable": true }, @@ -2031,7 +2030,7 @@ }, { "cell_type": "markdown", - "id": "c31bedcd", + "id": "aef181ad", "metadata": { "editable": true }, @@ -2050,7 +2049,7 @@ }, { "cell_type": "markdown", - "id": "6df0c334", + "id": "1d2d754e", "metadata": { "editable": true }, @@ -2063,7 +2062,7 @@ }, { "cell_type": "markdown", - "id": "de23d2ac", + "id": "c95ac16f", "metadata": { "editable": true }, @@ -2081,7 +2080,7 @@ }, { "cell_type": "markdown", - "id": "68361f19", + "id": "3307334e", "metadata": { "editable": true }, @@ -2092,7 +2091,7 @@ }, { "cell_type": "markdown", - "id": "f33a0407", + "id": "369d2469", "metadata": { "editable": true }, @@ -2111,7 +2110,7 @@ }, { "cell_type": "markdown", - "id": "28d4cb0f", + "id": "7e85af13", "metadata": { "editable": true }, @@ -2129,7 +2128,7 @@ }, { "cell_type": "markdown", - "id": "780f185a", + "id": "2f5a76de", "metadata": { "editable": true }, @@ -2142,7 +2141,7 @@ }, { "cell_type": "markdown", - "id": "9a17ac89", + "id": "9ccbf1ad", "metadata": { "editable": true }, @@ -2162,7 +2161,7 @@ }, { "cell_type": "markdown", - "id": "bfa341fe", + "id": "c7b1040e", "metadata": { "editable": true }, @@ -2195,7 +2194,7 @@ }, { "cell_type": "markdown", - "id": "bc15b63b", + "id": "b0247dde", "metadata": { "editable": true }, @@ -2207,7 +2206,7 @@ }, { "cell_type": "markdown", - "id": "eec4055a", + "id": "5dcac88d", "metadata": { "editable": true }, @@ -2226,7 +2225,7 @@ }, { "cell_type": "markdown", - "id": "feb4e6e6", + "id": "e03faed1", "metadata": { "editable": true }, @@ -2240,7 +2239,7 @@ }, { "cell_type": "markdown", - "id": "3ae2c264", + "id": "a764ce57", "metadata": { "editable": true }, @@ -2263,7 +2262,7 @@ }, { "cell_type": "markdown", - "id": "830f06e3", + "id": "b1cea08a", "metadata": { "editable": true }, @@ -2282,7 +2281,7 @@ }, { "cell_type": "markdown", - "id": "7f6872f0", + "id": "a2224849", "metadata": { "editable": true }, @@ -2294,7 +2293,7 @@ }, { "cell_type": "markdown", - "id": "120447fb", + "id": "b38f8f11", "metadata": { "editable": true }, @@ -2304,7 +2303,7 @@ }, { "cell_type": "markdown", - "id": "809db622", + "id": "e7e5e935", "metadata": { "editable": true }, @@ -2316,7 +2315,7 @@ }, { "cell_type": "markdown", - "id": "7a38a685", + "id": "e70ad6fb", "metadata": { "editable": true }, @@ -2333,7 +2332,7 @@ { "cell_type": "code", "execution_count": 24, - "id": "11e0216d", + "id": "68609907", "metadata": { "collapsed": false, "editable": true diff --git a/doc/src/week40/week40.do.txt b/doc/src/week40/week40.do.txt index 3a6096142..f44cf251a 100644 --- a/doc/src/week40/week40.do.txt +++ b/doc/src/week40/week40.do.txt @@ -8,7 +8,7 @@ DATE: September 29-October 3, 2025 ===== Lecture Monday September 30, 2024 ===== !bblock o Logistic regression and gradient descent, examples on how to code -o Stochastic Gradient descent and automatic differentiation, examples using Logistic regression +o Automatic differentiation and gradient descent, examples using Logistic regression o Start with the basics of Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model # o "Video of lecture":"https://youtu.be/jdJoOrCIdII" # o Whiteboard notes at URL:"https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember30.pdf" @@ -20,8 +20,8 @@ o Start with the basics of Neural Networks, setting up the basic steps, from the o The lecture notes for week 40 (these notes) o For a good discussion on gradient methods, we would like to recommend Goodfellow et al section 4.3-4.5 and sections 8.3-8.6. We will come back to the latter chapter in our discussion of Neural networks as well. o For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al chapter 2 (contains also material about gradient descent) and chapter 11 (we will use this next week) - o Video on gradient descent at URL:"https://www.youtube.com/watch?v=sDv4f4s2SB8" - o Video on stochastic gradient descent at URL:"https://www.youtube.com/watch?v=vMh0zPT0tLI" +# o Video on gradient descent at URL:"https://www.youtube.com/watch?v=sDv4f4s2SB8" + o Video on automatic differentiation at URL:"https://www.youtube.com/watch?v=wG_nF1awSSY" o Neural Networks demystified at URL:"https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs" o Building Neural Networks from scratch at URL:https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3&ab_channel=sentdex" !eblock