Created using Colab
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@@ -1,18 +1,16 @@
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{
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"cells": [
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"metadata": {
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"colab_type": "text",
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"id": "view-in-github"
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"id": "view-in-github",
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"colab_type": "text"
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},
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"source": [
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"<a href=\"https://colab.research.google.com/github/udlbook/udlbook/blob/main/Notebooks/Chap17/17_1_Latent_Variable_Models.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "t9vk9Elugvmi"
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@@ -43,7 +41,6 @@
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]
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {
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"id": "IyVn-Gi-p7wf"
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@@ -79,7 +76,6 @@
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]
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {
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"id": "KB9FU34onW1j"
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@@ -145,7 +141,6 @@
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {
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"id": "sQg2gKR5zMrF"
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@@ -223,7 +218,6 @@
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]
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {
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"id": "0X4NwixzqxtZ"
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@@ -254,7 +248,6 @@
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {
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"id": "25xqXnmFo-PH"
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@@ -281,7 +274,7 @@
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"# We can't integrate this function in closed form\n",
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"# So let's approximate it as a sum over the z values (z = np.arange(-3,3,0.01))\n",
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"# You will need the functions get_likelihood() and get_prior()\n",
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"# To make this a valid probability distribution, you need to divide\n",
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"# To make this a valid probability distribution, you need to multiply\n",
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"# By the z-increment (0.01)\n",
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"# Replace this line\n",
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"pr_x1_x2 = np.zeros_like(x1_mesh)\n",
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@@ -292,7 +285,6 @@
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {
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"id": "W264N7By_h9y"
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@@ -320,7 +312,6 @@
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {
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"id": "D7N7oqLe-eJO"
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@@ -388,9 +379,8 @@
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],
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"metadata": {
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"colab": {
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"authorship_tag": "ABX9TyOSEQVqxE5KrXmsZVh9M3gq",
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"include_colab_link": true,
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"provenance": []
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"provenance": [],
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"include_colab_link": true
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},
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"kernelspec": {
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"display_name": "Python 3",
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@@ -402,4 +392,4 @@
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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}
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