examples are automatically written updated 03_ml_intro.odp

notebooks/03_ml_basics_ex_1_magic.ipynb

@@ -206,7 +206,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -220,7 +220,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.5"
+   "version": "3.8.16"
   }
  },
  "nbformat": 4,

notebooks/03_ml_basics_ex_1_sol_magic.ipynb

@@ -445,7 +445,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -459,7 +459,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.5"
+   "version": "3.8.16"
   }
  },
  "nbformat": 4,

notebooks/03_ml_basics_ex_2_display_Cifar10_Greyscale.ipynb

@@ -91,6 +91,9 @@
    "outputs": [],
    "source": [
     "# Convert images to grayscale\n",
+    "# The ... notation is used to select all dimensions of the array up to the last one\n",
+    "# The vector [0.2989, 0.5870, 0.1140] converts a color image to grayscale by taking \n",
+    "# a weighted average of the color channels.\n",
     "train_images_gray = np.dot(x_train[..., :3], [0.2989, 0.5870, 0.1140])\n",
     "test_images_gray = np.dot(x_test[..., :3], [0.2989, 0.5870, 0.1140])"
    ]

notebooks/03_ml_basics_simple_neural_network.ipynb

@@ -1,7 +1,6 @@
 {
  "cells": [
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -24,7 +23,6 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -83,7 +81,6 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -100484,7 +100481,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.9"
+   "version": "3.8.16"
   },
   "vscode": {
    "interpreter": {