{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"
"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "r-xn3WLqP2wM"
},
"source": [
"# Video 9.2: Types of machine learning"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "T9ckFFHNP2wQ"
},
"source": [
"## Video"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"id": "fTCqwicVP2wQ",
"cellView": "form",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 449
},
"outputId": "64996263-429e-4273-cc0f-b3010570ca72",
"tags": [
"remove-input"
]
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Video available at https://youtube.com/watch?v=JXZGC0DPxKI\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
""
],
"text/html": [
"\n",
" \n",
" "
],
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},
"metadata": {},
"execution_count": 1
}
],
"source": [
"# @markdown\n",
"from IPython.display import YouTubeVideo\n",
"from ipywidgets import widgets\n",
"out = widgets.Output()\n",
"with out:\n",
" display(YouTubeVideo(id=f\"JXZGC0DPxKI\", width=730, height=410, fs=1))\n",
"display(out)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "XMhhhdFCP2wS"
},
"source": [
"## Notes\n",
"\n",
"\n",
" Click here to download notes\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"source": [
"
\n"
],
"metadata": {
"id": "P7tXrFlRKyGi"
}
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.8.13 ('mathtools')",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.13"
},
"orig_nbformat": 4,
"vscode": {
"interpreter": {
"hash": "2f26a17d6a9624f855b5f9e02ffdc0ae71c8577a2562f495dada4b6f29d8bdd3"
}
},
"colab": {
"provenance": [],
"collapsed_sections": [],
"include_colab_link": true
}
},
"nbformat": 4,
"nbformat_minor": 0
}