{ "cells": [ { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# Intro to Deep Learning 4\n", "## Neural Network Mathematics\n", "\n", "## Import Dependencies" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import datetime\n", "import numpy as np\n", "import pandas as pd\n", "from dateutil.parser import parse\n", "import matplotlib.pyplot as plt\n", "from sklearn.model_selection import train_test_split" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Masage Data\n", "In this step I am going to drop all of the columns that are not pertinent to our solution. I then will go about conver" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def normalize(column):\n", " min = column.min()\n", " max = column.max()\n", " column = (column - min)/(max - min)\n", " return column" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
| \n", " | Date | \n", "Time | \n", "Latitude | \n", "Longitude | \n", "Magnitude | \n", "NormMagnitude | \n", "Bias | \n", "
|---|---|---|---|---|---|---|---|
| 0 | \n", "0.000000 | \n", "0.572429 | \n", "0.590649 | \n", "0.904493 | \n", "6.0 | \n", "0.138889 | \n", "1 | \n", "
| 1 | \n", "0.000105 | \n", "0.479032 | \n", "0.484060 | \n", "0.853759 | \n", "5.8 | \n", "0.083333 | \n", "1 | \n", "
| 2 | \n", "0.000158 | \n", "0.754152 | \n", "0.346451 | \n", "0.016736 | \n", "6.2 | \n", "0.194444 | \n", "1 | \n", "
| 3 | \n", "0.000316 | \n", "0.784536 | \n", "0.110396 | \n", "0.434562 | \n", "5.8 | \n", "0.083333 | \n", "1 | \n", "
| 4 | \n", "0.000369 | \n", "0.564466 | \n", "0.545838 | \n", "0.851190 | \n", "5.8 | \n", "0.083333 | \n", "1 | \n", "
| 5 | \n", "0.000421 | \n", "0.567035 | \n", "0.390441 | \n", "0.962863 | \n", "6.7 | \n", "0.333333 | \n", "1 | \n", "
| 6 | \n", "0.000527 | \n", "0.564176 | \n", "0.640384 | \n", "0.744077 | \n", "5.9 | \n", "0.111111 | \n", "1 | \n", "
| 7 | \n", "0.000685 | \n", "0.970646 | \n", "0.391029 | \n", "0.961705 | \n", "6.0 | \n", "0.138889 | \n", "1 | \n", "
| 8 | \n", "0.000737 | \n", "0.480977 | \n", "0.126486 | \n", "0.424878 | \n", "6.0 | \n", "0.138889 | \n", "1 | \n", "
| 9 | \n", "0.000790 | \n", "0.446716 | \n", "0.322022 | \n", "0.995803 | \n", "5.8 | \n", "0.083333 | \n", "1 | \n", "