curriculum/ml_intro/recommendation-systems/simple_SVD_recommender.ipynb

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   "source": [
    "# A simple example of SVD for recommendation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   },
   "source": [
    "**Note: Before running this, have a read through. Some of the discussion is based on my particular randomly generated data**"
   ]
  },
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   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
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   "source": [
    "First, let's generate a really simple data set. Each row is a user, and each column is an item. If the value for a user:item location is 1; that user has \"liked\" that item on _SocialMediaster-SellingMaster<sup>TM</sup>_, my new social media platform for people who like items and things and stuff."
   ]
  },
  {
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       "       item0  item1  item2  item3  item4\n",
       "user0      0      1      0      0      0\n",
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       "user3      0      1      1      1      0\n",
       "user4      1      0      1      1      1\n",
       "user5      1      1      1      1      1\n",
       "user6      0      0      1      1      1\n",
       "user7      0      1      0      0      0\n",
       "user8      0      0      1      1      1\n",
       "user9      1      1      0      1      1"
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   "source": [
    "num_users = 10\n",
    "num_items = 5\n",
    "np.random.seed(42)\n",
    "def generate_users(num_users, num_items):\n",
    "    data = []\n",
    "    for i in range(num_users):\n",
    "        user = [np.random.randint(2) for _ in range(num_items)]\n",
    "        data.append(user)\n",
    "    return data\n",
    "cols = [\"item\"+str(i) for i in range(num_items)]\n",
    "rows = [\"user\"+str(i) for i in range(num_users)]\n",
    "user_item_mat = pd.DataFrame(generate_users(num_users,num_items), columns=cols)\n",
    "user_item_mat.index = rows\n",
    "user_item_mat         "
   ]
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   "cell_type": "markdown",
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   "source": [
    "Now, let's do some SVD. This is a small enough dataset that I really don't need to truncate... but in most large scale recommenders you WILL need to truncate, so we're going to start with only 3 components of SVD. "
   ]
  },
  {
   "cell_type": "code",
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   },
   "outputs": [],
   "source": [
    "from scipy.linalg import svd\n",
    "\n",
    "U, Sigma, VT = svd(user_item_mat)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As a reminder, here's what we're expecting to see:\n",
    "\n",
    "<img src=\"http://zwmiller.com/projects/images/svd_breakdown.png\">"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "Great, so now what do we have? In this case **VT** is now a matrix where each column represents one of the items in the new vector space. Each row is one component of the vector space, for the items."
   ]
  },
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       "          0         1         2         3         4\n",
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    "VT = VT[:3,:]\n",
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   "source": [
    "If I transpose this, the rows are items, and the columns are the items in the \"hidden\" vector space created by the truncated SVD."
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   "source": [
    "**U** is a matrix where each row is a user and each column shows the location in the hidden vector space created by the SVD."
   ]
  },
  {
   "cell_type": "code",
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   "source": [
    "U = U[:,:3]\n",
    "pd.DataFrame(U)"
   ]
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   "cell_type": "markdown",
   "metadata": {
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     "frozen": false,
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   "source": [
    "**Sigma** is just the singular values of the decomposition. In this case, we're not particularly interested in **Sigma**."
   ]
  },
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   "cell_type": "code",
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       "0  4.350384  0.000000  0.000000\n",
       "1  0.000000  1.954766  0.000000\n",
       "2  0.000000  0.000000  1.747531"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Sigma = Sigma[:3]\n",
    "pd.DataFrame(np.diag(Sigma))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simple example with named entities to show this method works"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-07T21:44:00.722826Z",
     "start_time": "2018-12-07T21:44:00.713321Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "data = [[5,4,5,0,0,0],[3,3,3,0,0,0],[5,5,5,0,0,0],[4,5,4,0,0,0],[0,0,0,3,3,3],[0,0,0,5,5,5],[0,0,0,4,5,4],[0,0,0,0,0,0]]\n",
    "df = pd.DataFrame(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-07T21:44:01.562012Z",
     "start_time": "2018-12-07T21:44:01.540124Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Star Wars</th>\n",
       "      <th>Star Trek</th>\n",
       "      <th>Space Balls</th>\n",
       "      <th>Diehard</th>\n",
       "      <th>Lethal Weapon</th>\n",
       "      <th>Terminator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>user0</th>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user1</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user2</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user3</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user5</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user6</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user7</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Star Wars  Star Trek  Space Balls  Diehard  Lethal Weapon  Terminator\n",
       "user0          5          4            5        0              0           0\n",
       "user1          3          3            3        0              0           0\n",
       "user2          5          5            5        0              0           0\n",
       "user3          4          5            4        0              0           0\n",
       "user4          0          0            0        3              3           3\n",
       "user5          0          0            0        5              5           5\n",
       "user6          0          0            0        4              5           4\n",
       "user7          0          0            0        0              0           0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols = ['Star Wars', 'Star Trek', 'Space Balls', 'Diehard','Lethal Weapon', 'Terminator']\n",
    "rows = [\"user\"+str(i) for i in range(8)]\n",
    "df.index = rows\n",
    "df.columns = cols\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-07T21:44:02.182243Z",
     "start_time": "2018-12-07T21:44:02.172123Z"
    }
   },
   "outputs": [],
   "source": [
    "from scipy.linalg import svd\n",
    "\n",
    "U_test, Sigma_test, VT_test = svd(df)\n",
    "VT_test = VT_test[:2,:]\n",
    "U_test = U_test[:,:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-07T21:44:03.156631Z",
     "start_time": "2018-12-07T21:44:03.139565Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Star Wars</th>\n",
       "      <td>-0.578215</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Star Trek</th>\n",
       "      <td>-0.575618</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Space Balls</th>\n",
       "      <td>-0.578215</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Diehard</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.561084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lethal Weapon</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.608580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Terminator</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.561084</td>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "                      0         1\n",
       "Star Wars     -0.578215  0.000000\n",
       "Star Trek     -0.575618  0.000000\n",
       "Space Balls   -0.578215  0.000000\n",
       "Diehard        0.000000 -0.561084\n",
       "Lethal Weapon  0.000000 -0.608580\n",
       "Terminator     0.000000 -0.561084"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie_concept_test = pd.DataFrame(VT_test, columns=cols)\n",
    "movie_concept_test.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-07T21:44:03.682450Z",
     "start_time": "2018-12-07T21:44:03.676652Z"
    }
   },
   "outputs": [],
   "source": [
    "user_concept_test = pd.DataFrame(U_test, index=rows)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-07T21:44:04.108385Z",
     "start_time": "2018-12-07T21:44:04.092178Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "      <th></th>\n",
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       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>user0</th>\n",
       "      <td>-0.540577</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user1</th>\n",
       "      <td>-0.347440</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user2</th>\n",
       "      <td>-0.579066</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user3</th>\n",
       "      <td>-0.501741</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user4</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.412328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user5</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.687214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user6</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.598100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user7</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              0         1\n",
       "user0 -0.540577  0.000000\n",
       "user1 -0.347440  0.000000\n",
       "user2 -0.579066  0.000000\n",
       "user3 -0.501741  0.000000\n",
       "user4  0.000000 -0.412328\n",
       "user5  0.000000 -0.687214\n",
       "user6  0.000000 -0.598100\n",
       "user7  0.000000  0.000000"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_concept_test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "## Now back to our normal data\n",
    "\n",
    "Now, let's take a look at the matrix again. \n",
    "\n",
    "Let's note a few things (assuming you are still looking at my data and haven't re-run anything yet):\n",
    " * Items 0 and 4 have a lot of overlapping users. Users that like Item 2, tend to also like Item 3.\n",
    " * Users 6 and 8 like exactly the same items."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-07T21:44:05.044945Z",
     "start_time": "2018-12-07T21:44:05.025890Z"
    },
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item0</th>\n",
       "      <th>item1</th>\n",
       "      <th>item2</th>\n",
       "      <th>item3</th>\n",
       "      <th>item4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>user0</th>\n",
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       "    <tr>\n",
       "      <th>user1</th>\n",
       "      <td>1</td>\n",
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       "      <th>user2</th>\n",
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       "      <td>0</td>\n",
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       "      <th>user3</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user5</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user6</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user7</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user8</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user9</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       item0  item1  item2  item3  item4\n",
       "user0      0      1      0      0      0\n",
       "user1      1      0      0      0      1\n",
       "user2      0      0      0      0      1\n",
       "user3      0      1      1      1      0\n",
       "user4      1      0      1      1      1\n",
       "user5      1      1      1      1      1\n",
       "user6      0      0      1      1      1\n",
       "user7      0      1      0      0      0\n",
       "user8      0      0      1      1      1\n",
       "user9      1      1      0      1      1"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_item_mat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-07T21:44:58.905689Z",
     "start_time": "2018-12-07T21:44:57.873401Z"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1440x1152 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "%matplotlib inline\n",
    "plt.style.use('seaborn')\n",
    "\n",
    "fig = plt.figure(figsize=(20,16))\n",
    "ax = fig.gca(projection='3d')\n",
    "ax.scatter(U[:,0],U[:,1],U[:,2],c='k',s=150);\n",
    "ax.set_xlabel(\"D1\", fontsize=20, labelpad=20)\n",
    "ax.set_ylabel(\"D2\", fontsize=20, labelpad=20)\n",
    "ax.set_zlabel(\"D3\", fontsize=20, labelpad=20);\n",
    "\n",
    "lbls = user_item_mat.index\n",
    "offset = 0.01\n",
    "for i, txt in enumerate(lbls):\n",
    "    if i not in [6,7]:\n",
    "        ax.text(U[i,0]+offset,U[i,1],U[i,2],txt, fontsize=20)\n",
    "    else:\n",
    "        ax.text(U[i,0]+offset,U[i,1],U[i,2]+5*offset,txt, fontsize=20)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-07T21:45:05.345177Z",
     "start_time": "2018-12-07T21:45:04.862131Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1152 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(20,16))\n",
    "ax = fig.gca(projection='3d')\n",
    "ax.scatter(VT.T[:,0],VT.T[:,1],VT.T[:,2],c='b',s=150, label=\"Items\");\n",
    "ax.scatter(U[:,0],U[:,1],U[:,2],c='r',s=150, label=\"Users\");\n",
    "ax.set_xlabel(\"D1\", fontsize=20, labelpad=20)\n",
    "ax.set_ylabel(\"D2\", fontsize=20, labelpad=20)\n",
    "ax.set_zlabel(\"D3\", fontsize=20, labelpad=20);\n",
    "\n",
    "lbls = user_item_mat.columns\n",
    "item_offset = 0.01\n",
    "for i, txt in enumerate(lbls):\n",
    "    if i not in [6,7]:\n",
    "        ax.text(VT.T[i,0],VT.T[i,1]+item_offset,VT.T[i,2],txt, fontsize=20)\n",
    "    else:\n",
    "        ax.text(VT.T[i,0],VT.T[i,1]+item_offset,VT.T[i,2]+5*item_offset,txt, fontsize=20)\n",
    "\n",
    "lbls = user_item_mat.index\n",
    "offset = 0.01\n",
    "for i, txt in enumerate(lbls):\n",
    "    if i not in [6,7]:\n",
    "        ax.text(U[i,0],U[i,1]+offset,U[i,2],txt, fontsize=20)\n",
    "    else:\n",
    "        ax.text(U[i,0],U[i,1]+offset,U[i,2]+6*offset,txt, fontsize=20)\n",
    "ax.view_init(30,15)\n",
    "plt.legend(loc=\"upper left\", fontsize=30);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "So, if we look in our new hidden vector space and take the dot products of items (cosine similarity!), we expect that items 2 & 3 are the most similar. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-07T21:45:15.275844Z",
     "start_time": "2018-12-07T21:45:15.265430Z"
    },
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Item 2 & 0:  -0.21039350295933443\n",
      "Item 2 & 1:  -0.033077064237217\n",
      "Item 2 & 3:  0.4411602025458312\n",
      "Item 2 & 4:  0.07975391765448048\n"
     ]
    }
   ],
   "source": [
    "compare_item = 2\n",
    "for item in range(num_items):\n",
    "    if item != compare_item:\n",
    "        print(\"Item %s & %s: \"%(compare_item,item), np.dot(VT.T[compare_item],VT.T[item]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "If we compare users, we expect that users 6 & 8 should be the most similar."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-07T21:45:16.830953Z",
     "start_time": "2018-12-07T21:45:16.823884Z"
    },
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "User 6 & 0:  -0.12062412584166123\n",
      "User 6 & 1:  -0.057081599294588406\n",
      "User 6 & 2:  0.03170861407870819\n",
      "User 6 & 3:  0.15405294677742892\n",
      "User 6 & 4:  0.21759547332450174\n",
      "User 6 & 5:  0.09697134748284053\n",
      "User 6 & 6:  0.3063856866977984\n",
      "User 6 & 7:  -0.12062412584166123\n",
      "User 6 & 8:  0.3063856866977984\n",
      "User 6 & 9:  -0.06923627200769757\n"
     ]
    }
   ],
   "source": [
    "compare_user = 6\n",
    "for user in range(num_users):\n",
    "    #if user != compare_user:\n",
    "        print(\"User %s & %s: \"%(compare_user,user), np.dot(U[compare_user],U[user]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "Let's make a function that returns recommendations for a given item input (this user likes item 0... so she'll probably also like items X, Y, Z)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-07T21:45:26.092254Z",
     "start_time": "2018-12-07T21:45:26.082870Z"
    },
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3, 4]\n"
     ]
    }
   ],
   "source": [
    "def get_recommends(itemID, VT, num_recom=2):\n",
    "    recs = []\n",
    "    for item in range(VT.T.shape[0]):\n",
    "        if item != itemID:\n",
    "            recs.append([item,np.dot(VT.T[itemID],VT.T[item])])\n",
    "    final_rec = [i[0] for i in sorted(recs,key=lambda x: x[1],reverse=True)]\n",
    "    return final_rec[:num_recom]\n",
    "\n",
    "print(get_recommends(2,VT,num_recom=2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "source": [
    "We could also find a user that's most similar to a user and then recommend all items they like. In my example, user 3 is most similar to user 5... but user 5 also likes item 0 (and user 3 doesn't). Thus, this function will find for user 3 - User 5 is most similar, and item 0 should be something user 3 likes too."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-07T21:47:24.047098Z",
     "start_time": "2018-12-07T21:47:24.008374Z"
    },
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "User #3's most similar user is User #5 \n",
      "Items for User 3 to check out:  [0, 4]\n"
     ]
    }
   ],
   "source": [
    "def get_recommends_user(userID, U, df):\n",
    "    userrecs = []\n",
    "    for user in range(U.shape[0]):\n",
    "        if user!= userID:\n",
    "            userrecs.append([user,np.dot(U[userID],U[user])])\n",
    "    final_rec = [i[0] for i in sorted(userrecs,key=lambda x: x[1],reverse=True)]\n",
    "    comp_user = final_rec[0]\n",
    "    print(\"User #%s's most similar user is User #%s \"% (userID, comp_user))\n",
    "    rec_likes = df.iloc[comp_user]\n",
    "    current = df.iloc[userID]\n",
    "    recs = []\n",
    "    for i,item in enumerate(current):\n",
    "        if item != rec_likes[i] and rec_likes[i]!=0:\n",
    "            recs.append(i)\n",
    "    return recs\n",
    "\n",
    "user_to_rec = 3\n",
    "print(\"Items for User %s to check out: \"% user_to_rec, get_recommends_user(user_to_rec,U,user_item_mat))"
   ]
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    "That's exactly what a recommender is doing for collaborative filtering, on a massive scale!"
   ]
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