Merge pull request #2 from Archiit19/BugFixNew

Bug Fixes in Lesson01 and Lesson 02

Author: Archiit19

Lesson01/Activity1.ipynb

@@ -1,5 +1,14 @@
 {
  "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pip install autocorrect"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -328,7 +337,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.8"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,

Lesson02/Exercise13.ipynb

@@ -20,6 +20,15 @@
     "iii) TextBlob<br>"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pip install textblob"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -220,7 +229,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,

Lesson02/Exercise14.ipynb

@@ -18,6 +18,15 @@
     "Sunil tweeted, “Witnessing 70th Republic Day of India from Rajpath, New Delhi. Mesmerizing performance by Indian Army! Awesome airshow! @india_official @indian_army  #India #70thRepublic_Day. For more photos ping me sunil@photoking.com :) ”"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pip install keras tensorflow"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 2,
@@ -133,7 +142,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,

Lesson02/Exercise27.ipynb

@@ -20,7 +20,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#!pip install WordCloud"
+    "pip install WordCloud"
    ]
   },
   {
@@ -123,7 +123,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,

Lesson02/Exercise28.ipynb

@@ -21,7 +21,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#!pip install spacy"
+    "pip install spacy"
    ]
   },
   {
@@ -30,7 +30,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#!python -m spacy download en"
+    "python -m spacy download en"
    ]
   },
   {
@@ -201,7 +201,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,

Lesson03/Activity5.ipynb

@@ -24,6 +24,26 @@
     "The dataset under CC0, with the underlying comment text being governed by Wikipedia's CC-SA-3.0"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: xgboost in c:\\python\\python37\\lib\\site-packages (0.82)\n",
+      "Requirement already satisfied: numpy in c:\\python\\python37\\lib\\site-packages (from xgboost) (1.16.2)\n",
+      "Requirement already satisfied: scipy in c:\\python\\python37\\lib\\site-packages (from xgboost) (1.2.1)\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip install xgboost"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -955,7 +975,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,

Lesson03/Exercise30.ipynb

@@ -8,6 +8,15 @@
     "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."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pip install seaborn"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 5,
@@ -525,7 +534,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,

Lesson03/Exercise34.ipynb

@@ -17,6 +17,24 @@
     "3) Multi-stage sampling<br>"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: xlrd in c:\\python\\python37\\lib\\site-packages (1.2.0)\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip install xlrd"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 6,
@@ -508,7 +526,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,

Lesson03/Exercise39.ipynb

@@ -19,7 +19,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#!pip install joblib"
+    "pip install joblib"
    ]
   },
   {
@@ -188,7 +188,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,