Update notebooks for Google Colab compatability

1_image_classification.ipynb

@@ -64,30 +64,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "num_train_samples = 50000\n",
+    "from keras.datasets import cifar10\n",
-    "\n",
+    "(x_train, y_train), (x_test, y_test) = cifar10.load_data()"
-    "x_train = np.empty((num_train_samples, 3, 32, 32), dtype=\"uint8\")\n",
-    "y_train = np.empty((num_train_samples,), dtype=\"uint8\")\n",
-    "\n",
-    "for i in range(1, 6):\n",
-    "    file_path = os.path.join(\"cifar-10-batches-py\", f\"data_batch_{i}\")\n",
-    "    (\n",
-    "        x_train[(i - 1) * 10000 : i * 10000, :, :, :],\n",
-    "        y_train[(i - 1) * 10000 : i * 10000],\n",
-    "    ) = load_batch(file_path)\n",
-    "\n",
-    "file_path = os.path.join(\"cifar-10-batches-py\", \"test_batch\")\n",
-    "x_test, y_test = load_batch(file_path)\n",
-    "\n",
-    "y_train = np.reshape(y_train, (len(y_train), 1))\n",
-    "y_test = np.reshape(y_test, (len(y_test), 1))\n",
-    "\n",
-    "if backend.image_data_format() == \"channels_last\":\n",
-    "    x_train = x_train.transpose(0, 2, 3, 1)\n",
-    "    x_test = x_test.transpose(0, 2, 3, 1)\n",
-    "\n",
-    "x_test = x_test.astype(x_train.dtype)\n",
-    "y_test = y_test.astype(y_train.dtype)"
    ]
   },
   {
@@ -151,8 +129,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "y_train_one_hot = keras.src.utils.numerical_utils.to_categorical(y_train, 10)\n",
+    "y_train_one_hot = keras.utils.to_categorical(y_train, 10)\n",
-    "y_test_one_hot = keras.src.utils.numerical_utils.to_categorical(y_test, 10)"
+    "y_test_one_hot = keras.utils.to_categorical(y_test, 10)"
    ]
   },
   {
@@ -278,6 +256,15 @@
     "Let's try and feed a picture of a cat to the model, and see what it thinks... As a reminder, the model hasn't been trained on pictures of cats."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!wget -O cat.jpg https://git.subspace.solutions/cads/ai-lesson-resources/media/branch/main/cat.jpg"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,

2_reinforcement_learning.ipynb

@@ -20,6 +20,16 @@
     "## Import the packages 📦"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!apt-get update && apt-get install -y build-essential cmake swig\n",
+    "!pip install stable-baselines3\\[extra\\]==2.3.2 gymnasium\\[box2d\\]==0.29.1"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -407,6 +417,15 @@
     "\n",
     "Is moon landing too boring for you? Try to **change the environment**, why not use MountainCar-v0, CartPole-v1 or CarRacing-v0? Check how they work [using the gym documentation](https://www.gymlibrary.dev/) and have fun 🎉."
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!wget -O ppo-LunarLander-v2-good.zip https://git.subspace.solutions/cads/ai-lesson-resources/media/branch/main/ppo-LunarLander-v2-good.zip"
+   ]
   }
  ],
  "metadata": {

Dockerfile

@@ -1,24 +0,0 @@
-FROM docker.io/library/ubuntu:22.04
-
-ENV DEBIAN_FRONTEND noninteractive
-
-RUN apt-get update \
-	    && apt-get install -y --no-install-recommends apt-utils build-essential g++ curl cmake zlib1g-dev libjpeg-dev xvfb xorg-dev libboost-all-dev libsdl2-dev swig python3 python3-dev python3-future python3-pip python3-setuptools python3-wheel python3-tk libatlas-base-dev cython3 \
-	&& apt-get clean \
-	&& rm -rf /var/lib/apt/lists/*
-
-RUN python3 -m pip install --upgrade pip \
-	&& python3 -m pip install jupyterlab keras==3.3.3 matplotlib==3.9.0 numpy==1.26.4 tensorflow==2.16.1 scikit-image==0.22.0 \
-	&& python3 -m pip install "gymnasium[box2d]==0.29.1" "stable-baselines3[extra]==2.3.2"
-
-RUN apt-get update && apt-get install -y wget
-
-WORKDIR /work
-COPY . /work
-RUN /work/download-data.sh \
-	&& rm /work/*_solutions.ipynb
-
-ENV DEBIAN_FRONTEND teletype
-
-CMD xvfb-run -s "-screen 0 1400x900x24" \
-	/usr/local/bin/jupyter lab --port 8888 --ip=0.0.0.0 --allow-root

download-data.sh

@@ -1,4 +0,0 @@
-#!/bin/bash
-wget -O cifar-10-python.tar.gz https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz
-tar -xvf cifar-10-python.tar.gz
-rm cifar-10-python.tar.gz