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Archit Agarwal
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Lesson 3 Fixes. - Copied excel file outside the zipped folder.
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Lesson03/Activity5.ipynb

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"The dataset under CC0, with the underlying comment text being governed by Wikipedia's CC-SA-3.0"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Requirement already satisfied: xgboost in c:\\python\\python37\\lib\\site-packages (0.82)\n",
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"Requirement already satisfied: numpy in c:\\python\\python37\\lib\\site-packages (from xgboost) (1.16.2)\n",
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"Requirement already satisfied: scipy in c:\\python\\python37\\lib\\site-packages (from xgboost) (1.2.1)\n",
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"Note: you may need to restart the kernel to use updated packages.\n"
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]
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}
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],
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"source": [
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"pip install xgboost"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.1"
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"version": "3.7.3"
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}
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},
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"nbformat": 4,

Lesson03/Exercise30.ipynb

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"Create four clusters from text documents of sklearn's “The 20 newsgroups text dataset” using K-means clustering. Compare it with their actual categories. Use elbow method to obtain the optimal number of clusters."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"pip install seaborn"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.1"
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"version": "3.7.3"
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}
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},
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"nbformat": 4,

Lesson03/Exercise34.ipynb

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"3) Multi-stage sampling<br>"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Requirement already satisfied: xlrd in c:\\python\\python37\\lib\\site-packages (1.2.0)\n",
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"Note: you may need to restart the kernel to use updated packages.\n"
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]
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}
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],
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"source": [
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"pip install xlrd"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.1"
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"version": "3.7.3"
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}
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},
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"nbformat": 4,

Lesson03/Exercise39.ipynb

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"metadata": {},
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"outputs": [],
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"source": [
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"#!pip install joblib"
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"pip install joblib"
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]
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},
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{
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.1"
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"version": "3.7.3"
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}
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},
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"nbformat": 4,

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