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Latent Dirichlet Allocation
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tuanavu committed Jul 27, 2016
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Latent Dirichlet Allocation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Question 1\n",
"\n",
"<img src=\"images/Screen Shot 2016-07-27 at 9.28.49 AM.png\">\n",
"\n",
"*Screenshot taken from [Coursera](https://www.coursera.org/learn/ml-clustering-and-retrieval/exam/d6s1W/latent-dirichlet-allocation)*\n",
"\n",
"<!--TEASER_END-->"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Question 2\n",
"\n",
"<img src=\"images/Screen Shot 2016-07-27 at 9.28.52 AM.png\">\n",
"\n",
"*Screenshot taken from [Coursera](https://www.coursera.org/learn/ml-clustering-and-retrieval/exam/d6s1W/latent-dirichlet-allocation)*\n",
"\n",
"<!--TEASER_END-->"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Question 3\n",
"\n",
"<img src=\"images/Screen Shot 2016-07-27 at 9.29.00 AM.png\">\n",
"\n",
"*Screenshot taken from [Coursera](https://www.coursera.org/learn/ml-clustering-and-retrieval/exam/d6s1W/latent-dirichlet-allocation)*\n",
"\n",
"<!--TEASER_END-->"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Question 4\n",
"\n",
"<img src=\"images/Screen Shot 2016-07-27 at 9.31.39 AM.png\">\n",
"\n",
"*Screenshot taken from [Coursera](https://www.coursera.org/learn/ml-clustering-and-retrieval/exam/d6s1W/latent-dirichlet-allocation)*\n",
"\n",
"<!--TEASER_END-->"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Question 5\n",
"\n",
"<img src=\"images/Screen Shot 2016-07-27 at 9.31.44 AM.png\">\n",
"\n",
"*Screenshot taken from [Coursera](https://www.coursera.org/learn/ml-clustering-and-retrieval/exam/d6s1W/latent-dirichlet-allocation)*\n",
"\n",
"<!--TEASER_END-->"
]
}
],
"metadata": {
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"display_name": "Python 2",
"language": "python",
"name": "python2"
},
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"codemirror_mode": {
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"version": 2
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.11"
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"toc": {
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"toc_number_sections": false,
"toc_threshold": "8",
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"nbformat": 4,
"nbformat_minor": 0
}
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Original file line number Diff line number Diff line change
@@ -0,0 +1,103 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Latent Dirichlet Allocation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Question 1\n",
"\n",
"<img src=\"images/Screen Shot 2016-07-27 at 9.28.49 AM.png\">\n",
"\n",
"*Screenshot taken from [Coursera](https://www.coursera.org/learn/ml-clustering-and-retrieval/exam/d6s1W/latent-dirichlet-allocation)*\n",
"\n",
"<!--TEASER_END-->"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Question 2\n",
"\n",
"<img src=\"images/Screen Shot 2016-07-27 at 9.28.52 AM.png\">\n",
"\n",
"*Screenshot taken from [Coursera](https://www.coursera.org/learn/ml-clustering-and-retrieval/exam/d6s1W/latent-dirichlet-allocation)*\n",
"\n",
"<!--TEASER_END-->"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Question 3\n",
"\n",
"<img src=\"images/Screen Shot 2016-07-27 at 9.29.00 AM.png\">\n",
"\n",
"*Screenshot taken from [Coursera](https://www.coursera.org/learn/ml-clustering-and-retrieval/exam/d6s1W/latent-dirichlet-allocation)*\n",
"\n",
"<!--TEASER_END-->"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Question 4\n",
"\n",
"<img src=\"images/Screen Shot 2016-07-27 at 9.31.39 AM.png\">\n",
"\n",
"*Screenshot taken from [Coursera](https://www.coursera.org/learn/ml-clustering-and-retrieval/exam/d6s1W/latent-dirichlet-allocation)*\n",
"\n",
"<!--TEASER_END-->"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Question 5\n",
"\n",
"<img src=\"images/Screen Shot 2016-07-27 at 9.31.44 AM.png\">\n",
"\n",
"*Screenshot taken from [Coursera](https://www.coursera.org/learn/ml-clustering-and-retrieval/exam/d6s1W/latent-dirichlet-allocation)*\n",
"\n",
"<!--TEASER_END-->"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.11"
},
"toc": {
"toc_cell": false,
"toc_number_sections": false,
"toc_threshold": "8",
"toc_window_display": false
}
},
"nbformat": 4,
"nbformat_minor": 0
}

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