Recommender System/Recommender System.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "17112708",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: strsim in /home/ayush/.local/lib/python3.8/site-packages (0.0.3)\n"
     ]
    }
   ],
   "source": [
    "!pip install strsim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "53ab94cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Libraries required\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import string\n",
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "from similarity.cosine import Cosine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ddcddcde",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Reading and storing the csv file\n",
    "df = pd.read_csv(\"Dataset.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "75bb10d7",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>Course Name</th>\n",
       "      <th>University / Industry Partner Name</th>\n",
       "      <th>Difficulty Level</th>\n",
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       "      <th>Course URL</th>\n",
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       "      <th>all_skill</th>\n",
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       "      <td>https://www.coursera.org/learn/write-a-feature...</td>\n",
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       "      <th>4500</th>\n",
       "      <td>Global China: From the Mongols to the Ming</td>\n",
       "      <td>Harvard University</td>\n",
       "      <td>Beginner</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://www.edx.org/course/global-china-from-t...</td>\n",
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       "      <th>4501</th>\n",
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       "      <td>Learn about the latest in prevention, police a...</td>\n",
       "      <td>The high rates of crime and violence are two o...</td>\n",
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       "    <tr>\n",
       "      <th>4502</th>\n",
       "      <td>Computational Neuroscience: Neuronal Dynamics ...</td>\n",
       "      <td>École polytechnique fédérale de Lausanne</td>\n",
       "      <td>Advanced</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://www.edx.org/course/computational-neuro...</td>\n",
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      "text/plain": [
       "                                            Course Name  \\\n",
       "0     Write A Feature Length Screenplay For Film Or ...   \n",
       "1     Business Strategy: Business Model Canvas Analy...   \n",
       "2                         Silicon Thin Film Solar Cells   \n",
       "3                                  Finance for Managers   \n",
       "4          Retrieve Data using Single-Table SQL Queries   \n",
       "...                                                 ...   \n",
       "4500         Global China: From the Mongols to the Ming   \n",
       "4501  Leaders in Citizen Security and Justice Manage...   \n",
       "4502  Computational Neuroscience: Neuronal Dynamics ...   \n",
       "4503  Cities and the Challenge of Sustainable Develo...   \n",
       "4504                      MathTrackX: Special Functions   \n",
       "\n",
       "            University / Industry Partner Name Difficulty Level Course Rating  \\\n",
       "0                    Michigan State University         Beginner           4.8   \n",
       "1                     Coursera Project Network         Beginner           4.8   \n",
       "2                          �cole Polytechnique         Advanced           4.1   \n",
       "3                         IESE Business School     Intermediate           4.8   \n",
       "4                     Coursera Project Network         Beginner           4.6   \n",
       "...                                        ...              ...           ...   \n",
       "4500                        Harvard University         Beginner           NaN   \n",
       "4501           Inter-American Development Bank     Intermediate           NaN   \n",
       "4502  École polytechnique fédérale de Lausanne         Advanced           NaN   \n",
       "4503                               SDG Academy         Beginner           NaN   \n",
       "4504                    University of Adelaide         Beginner           NaN   \n",
       "\n",
       "                                             Course URL  \\\n",
       "0     https://www.coursera.org/learn/write-a-feature...   \n",
       "1     https://www.coursera.org/learn/canvas-analysis...   \n",
       "2     https://www.coursera.org/learn/silicon-thin-fi...   \n",
       "3     https://www.coursera.org/learn/operational-fin...   \n",
       "4     https://www.coursera.org/learn/single-table-sq...   \n",
       "...                                                 ...   \n",
       "4500  https://www.edx.org/course/global-china-from-t...   \n",
       "4501  https://www.edx.org/course/leaders-in-citizen-...   \n",
       "4502  https://www.edx.org/course/computational-neuro...   \n",
       "4503  https://www.edx.org/course/cities-and-the-chal...   \n",
       "4504  https://www.edx.org/course/mathtrackx-special-...   \n",
       "\n",
       "                                     Course Description  \\\n",
       "0     Write a Full Length Feature Film Script  In th...   \n",
       "1     By the end of this guided project, you will be...   \n",
       "2     This course consists of a general presentation...   \n",
       "3     When it comes to numbers, there is always more...   \n",
       "4     In this course you�ll learn how to effectively...   \n",
       "...                                                 ...   \n",
       "4500  Explore the impact of the conquest dynasties a...   \n",
       "4501  Learn about the latest in prevention, police a...   \n",
       "4502  This course explains the mathematical and comp...   \n",
       "4503  What is a sustainable city? Learn the basics h...   \n",
       "4504  Understand trigonometric, exponential and loga...   \n",
       "\n",
       "                                              all_skill  \n",
       "0     Drama  Comedy  peering  screenwriting  film  D...  \n",
       "1     Finance  business plan  persona (user experien...  \n",
       "2     chemistry  physics  Solar Energy  film  lambda...  \n",
       "3     accounts receivable  dupont analysis  analysis...  \n",
       "4     Data Analysis  select (sql)  database manageme...  \n",
       "...                                                 ...  \n",
       "4500  In the 13th century, by force of arms, the Mon...  \n",
       "4501  The high rates of crime and violence are two o...  \n",
       "4502  What happens in your brain when you make a dec...  \n",
       "4503  According to the United Nations, urbanization ...  \n",
       "4504  This course is part two of the MathTrackX XSer...  \n",
       "\n",
       "[4505 rows x 7 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Printing the datset\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "deca8a8e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#dropping Nan values\n",
    "df = df.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b960e1d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Function to retrieve a particular difficulty level\n",
    "def course_difficulty(level):\n",
    "    data = df.copy().loc[df['Difficulty Level']==level]\n",
    "    data['index'] = np.arange(0, data.shape[0])\n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "44b00549",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Function to clean the data by removing punctutions to increase the efficiency\n",
    "def remove_punctuations(text):\n",
    "    text = str(text) \n",
    "    for punctuation in string.punctuation:\n",
    "        text = text.replace(punctuation, '')\n",
    "    return text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "65ee0aea",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Function to find similarity between the course name entered by the user and existing courses in the dataset\n",
    "def recommender_course(name):\n",
    "    #Cosine similarity is a metric used to measure how similar the documents\n",
    "    #Mathematically, it measures the cosine of the angle between two vectors projected in a multi-dimensional space.\n",
    "    cosine = Cosine(2)\n",
    "    df[\"name\"] = name\n",
    "    df[\"p0\"] = df[\"name\"].apply(lambda s: cosine.get_profile(s)) \n",
    "    df[\"p1\"] = (df[\"Course Name\"]).apply(lambda s: cosine.get_profile(s)) \n",
    "    df[\"cosine_sim\"] = [cosine.similarity_profiles(p0,p1) for p0,p1 in zip(df[\"p0\"],df[\"p1\"])]\n",
    "    df.drop([\"p0\", \"p1\"], axis=1,inplace =  True)\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a6c62dbf",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Function to find similarity between the skill entered by the user and existing skills in the dataset\n",
    "def recommender_system(skill):\n",
    "     #Cosine similarity is a metric used to measure how similar the documents\n",
    "    #Mathematically, it measures the cosine of the angle between two vectors projected in a multi-dimensional space.\n",
    "    cosine = Cosine(2)\n",
    "    data[\"skill\"] = skill\n",
    "    data[\"p0\"] = data[\"skill\"].apply(lambda s: cosine.get_profile(s)) \n",
    "    data[\"p1\"] = data[\"new_column\"].apply(lambda s: cosine.get_profile(s)) \n",
    "    data[\"cosine_sim2\"] = [cosine.similarity_profiles(p0,p1) for p0,p1 in zip(data[\"p0\"],data[\"p1\"])]\n",
    "    data.drop([\"p0\", \"p1\"], axis=1,inplace =  True)\n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "36e463af",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "enter Yes to get previous course suggestion as well\n",
      "Yes\n"
     ]
    }
   ],
   "source": [
    "#counter to variable to check whether user wants to give his previous course done \n",
    "print(\"enter Yes to get previous course suggestion as well\")\n",
    "ctr = input()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "bddc845c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Yes\n",
      "Enter previous course\n",
      "Finance for managers\n",
      "Enter your level\n",
      "Beginner\n",
      "Enter previous skill: Finance\n"
     ]
    }
   ],
   "source": [
    "print(ctr)\n",
    "if(ctr == \"Yes\"):\n",
    "    #if the user gives his previous course then input is taken about it\n",
    "    print(\"Enter previous course\")\n",
    "    previous_course = input()\n",
    "    #The course entered is passed to the function to see similar courses\n",
    "    final = recommender_course(previous_course)\n",
    "    final\n",
    "    #Sorting the dataset in decreasing order of similarity w.r.t the course done by the user\n",
    "    final = final.sort_values('cosine_sim', ascending = False)\n",
    "    #Retrieve the top 1000 similar courses\n",
    "    df = final[0:1000] \n",
    "    #Takes the input from user about his level of learning\n",
    "    print(\"Enter your level\")\n",
    "    level = input()\n",
    "    #Level is passsed to the function to retrieve the corresponding courses w.r.t the level\n",
    "    data = course_difficulty(level)\n",
    "    data\n",
    "    #Concating the dataset to make a new column for further analysis\n",
    "    data['final'] = data['all_skill'] + data['Course Description'] + data['Course Name']\n",
    "    #Cleaning the dataset\n",
    "    data['new_column'] = data['final'].apply(remove_punctuations)\n",
    "    data\n",
    "    #Taking the skill the user wants to learn\n",
    "    skill = input('Enter previous skill: ')\n",
    "    #passing the skill to the function to get similar courses\n",
    "    final = recommender_system(skill)\n",
    "    #Sorting the courses in decreasing order of similarity\n",
    "    data = data.sort_values('cosine_sim2', ascending = False)\n",
    "else:\n",
    "    print(\"Enter your level\")\n",
    "    #Takes the input from user about his level of learning\n",
    "    level = input()\n",
    "    #Level is passsed to the function to retrieve the corresponding courses w.r.t the level\n",
    "    data = course_difficulty(level)\n",
    "    data\n",
    "    #Concating the dataset to make a new column for further analysis\n",
    "    data['final'] = data['all_skill'] + data['Course Description'] + data['Course Name']\n",
    "    #Cleaning the dataset\n",
    "    data['new_column'] = data['final'].apply(remove_punctuations)\n",
    "    #Taking the skill the user wants to learn\n",
    "    skill = input('Enter previous skill: ')\n",
    "    #passing the skill to the function to get similar courses\n",
    "    final = recommender_system(skill)\n",
    "    #Sorting the courses in decreasing order of similarity\n",
    "    data = data.sort_values('cosine_sim2', ascending = False)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "873c205e",
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Course Name</th>\n",
       "      <th>University / Industry Partner Name</th>\n",
       "      <th>Difficulty Level</th>\n",
       "      <th>Course Rating</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2829</th>\n",
       "      <td>Accounting: Principles of Financial Accounting</td>\n",
       "      <td>IESE Business School</td>\n",
       "      <td>Beginner</td>\n",
       "      <td>4.8</td>\n",
       "      <td>https://www.coursera.org/learn/financial-accou...</td>\n",
       "      <td>Financial Accounting is often called the langu...</td>\n",
       "      <td>income statement  analysis  cash flow  Finance...</td>\n",
       "      <td>Finance for managers</td>\n",
       "      <td>0.280945</td>\n",
       "      <td>135</td>\n",
       "      <td>income statement  analysis  cash flow  Finance...</td>\n",
       "      <td>income statement  analysis  cash flow  Finance...</td>\n",
       "      <td>Finance</td>\n",
       "      <td>0.495549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>834</th>\n",
       "      <td>FinTech Risk Management</td>\n",
       "      <td>The Hong Kong University of Science and Techno...</td>\n",
       "      <td>Beginner</td>\n",
       "      <td>4.6</td>\n",
       "      <td>https://www.coursera.org/learn/fintech-risk-ma...</td>\n",
       "      <td>This course �FinTech Risk Management� help you...</td>\n",
       "      <td>financial institution  Leadership and Manageme...</td>\n",
       "      <td>Finance for managers</td>\n",
       "      <td>0.390360</td>\n",
       "      <td>37</td>\n",
       "      <td>financial institution  Leadership and Manageme...</td>\n",
       "      <td>financial institution  Leadership and Manageme...</td>\n",
       "      <td>Finance</td>\n",
       "      <td>0.547142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>419</th>\n",
       "      <td>Finance for Non-Financial Managers</td>\n",
       "      <td>Emory University</td>\n",
       "      <td>Beginner</td>\n",
       "      <td>4.2</td>\n",
       "      <td>https://www.coursera.org/learn/finance-for-non...</td>\n",
       "      <td>Finance is for �Non-financial Managers� who wa...</td>\n",
       "      <td>balance sheet  income statement  income  prese...</td>\n",
       "      <td>Finance for managers</td>\n",
       "      <td>0.818923</td>\n",
       "      <td>0</td>\n",
       "      <td>balance sheet  income statement  income  prese...</td>\n",
       "      <td>balance sheet  income statement  income  prese...</td>\n",
       "      <td>Finance</td>\n",
       "      <td>0.565221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1164</th>\n",
       "      <td>Corporate Finance Essentials</td>\n",
       "      <td>IESE Business School</td>\n",
       "      <td>Beginner</td>\n",
       "      <td>4.8</td>\n",
       "      <td>https://www.coursera.org/learn/corporate-finan...</td>\n",
       "      <td>Corporate Finance Essentials will enable you t...</td>\n",
       "      <td>Economics  Finance  investment  evaluation  Ec...</td>\n",
       "      <td>Finance for managers</td>\n",
       "      <td>0.419961</td>\n",
       "      <td>19</td>\n",
       "      <td>Economics  Finance  investment  evaluation  Ec...</td>\n",
       "      <td>Economics  Finance  investment  evaluation  Ec...</td>\n",
       "      <td>Finance</td>\n",
       "      <td>0.513063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2068</th>\n",
       "      <td>Principles of Sustainable Finance</td>\n",
       "      <td>Erasmus University Rotterdam</td>\n",
       "      <td>Beginner</td>\n",
       "      <td>4.7</td>\n",
       "      <td>https://www.coursera.org/learn/sustainable-fin...</td>\n",
       "      <td>Finance is widely seen as an obstacle to a bet...</td>\n",
       "      <td>environmental factor  corporate governance  Fi...</td>\n",
       "      <td>Finance for managers</td>\n",
       "      <td>0.443039</td>\n",
       "      <td>13</td>\n",
       "      <td>environmental factor  corporate governance  Fi...</td>\n",
       "      <td>environmental factor  corporate governance  Fi...</td>\n",
       "      <td>Finance</td>\n",
       "      <td>0.526755</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         Course Name  \\\n",
       "2829  Accounting: Principles of Financial Accounting   \n",
       "834                          FinTech Risk Management   \n",
       "419               Finance for Non-Financial Managers   \n",
       "1164                    Corporate Finance Essentials   \n",
       "2068               Principles of Sustainable Finance   \n",
       "\n",
       "                     University / Industry Partner Name Difficulty Level  \\\n",
       "2829                               IESE Business School         Beginner   \n",
       "834   The Hong Kong University of Science and Techno...         Beginner   \n",
       "419                                    Emory University         Beginner   \n",
       "1164                               IESE Business School         Beginner   \n",
       "2068                       Erasmus University Rotterdam         Beginner   \n",
       "\n",
       "     Course Rating                                         Course URL  \\\n",
       "2829           4.8  https://www.coursera.org/learn/financial-accou...   \n",
       "834            4.6  https://www.coursera.org/learn/fintech-risk-ma...   \n",
       "419            4.2  https://www.coursera.org/learn/finance-for-non...   \n",
       "1164           4.8  https://www.coursera.org/learn/corporate-finan...   \n",
       "2068           4.7  https://www.coursera.org/learn/sustainable-fin...   \n",
       "\n",
       "                                     Course Description  \\\n",
       "2829  Financial Accounting is often called the langu...   \n",
       "834   This course �FinTech Risk Management� help you...   \n",
       "419   Finance is for �Non-financial Managers� who wa...   \n",
       "1164  Corporate Finance Essentials will enable you t...   \n",
       "2068  Finance is widely seen as an obstacle to a bet...   \n",
       "\n",
       "                                              all_skill                  name  \\\n",
       "2829  income statement  analysis  cash flow  Finance...  Finance for managers   \n",
       "834   financial institution  Leadership and Manageme...  Finance for managers   \n",
       "419   balance sheet  income statement  income  prese...  Finance for managers   \n",
       "1164  Economics  Finance  investment  evaluation  Ec...  Finance for managers   \n",
       "2068  environmental factor  corporate governance  Fi...  Finance for managers   \n",
       "\n",
       "      cosine_sim  index                                              final  \\\n",
       "2829    0.280945    135  income statement  analysis  cash flow  Finance...   \n",
       "834     0.390360     37  financial institution  Leadership and Manageme...   \n",
       "419     0.818923      0  balance sheet  income statement  income  prese...   \n",
       "1164    0.419961     19  Economics  Finance  investment  evaluation  Ec...   \n",
       "2068    0.443039     13  environmental factor  corporate governance  Fi...   \n",
       "\n",
       "                                             new_column    skill  cosine_sim2  \n",
       "2829  income statement  analysis  cash flow  Finance...  Finance     0.495549  \n",
       "834   financial institution  Leadership and Manageme...  Finance     0.547142  \n",
       "419   balance sheet  income statement  income  prese...  Finance     0.565221  \n",
       "1164  Economics  Finance  investment  evaluation  Ec...  Finance     0.513063  \n",
       "2068  environmental factor  corporate governance  Fi...  Finance     0.526755  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#To show the top 5 courses by selecting 5 random from the top 8 similar courses\n",
    "data[0:8].sample(n=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "42a192f6",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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