diff --git a/1_Image_Representation/.ipynb_checkpoints/1. Images as Numerical Data-checkpoint.ipynb b/1_Image_Representation/.ipynb_checkpoints/1. Images as Numerical Data-checkpoint.ipynb
deleted file mode 100644
index 2e99428..0000000
--- a/1_Image_Representation/.ipynb_checkpoints/1. Images as Numerical Data-checkpoint.ipynb	
+++ /dev/null
@@ -1,144 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Images as Grids of Pixels"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Import resources"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import matplotlib.image as mpimg  # for reading in images\n",
-    "\n",
-    "import matplotlib.pyplot as plt\n",
-    "import cv2  # computer vision library\n",
-    "\n",
-    "%matplotlib inline"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Read in and display the image"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Read in the image\n",
-    "image = mpimg.imread('images/waymo_car.jpg')\n",
-    "\n",
-    "# Print out the image dimensions\n",
-    "print('Image dimensions:', image.shape)\n",
-    "\n",
-    "# Change from color to grayscale\n",
-    "gray_image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)\n",
-    "\n",
-    "plt.imshow(gray_image, cmap='gray')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Print specific grayscale pixel values\n",
-    "# What is the pixel value at x = 400 and y = 300 (on the body of the car)?\n",
-    "\n",
-    "x = 400\n",
-    "y = 300\n",
-    "\n",
-    "print(gray_image[y,x])\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#Find the maximum and minimum grayscale values in this image\n",
-    "\n",
-    "max_val = np.amax(gray_image)\n",
-    "min_val = np.amin(gray_image)\n",
-    "\n",
-    "print('Max: ', max_val)\n",
-    "print('Min: ', min_val)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Create a 5x5 image using just grayscale, numerical values\n",
-    "tiny_image = np.array([[0, 20, 30, 150, 120],\n",
-    "                      [200, 200, 250, 70, 3],\n",
-    "                      [50, 180, 85, 40, 90],\n",
-    "                      [240, 100, 50, 255, 10],\n",
-    "                      [30, 0, 75, 190, 220]])\n",
-    "\n",
-    "# To show the pixel grid, use matshow\n",
-    "plt.matshow(tiny_image, cmap='gray')\n",
-    "\n",
-    "## TODO: See if you can draw a tiny smiley face or something else!"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "anaconda-cloud": {},
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.4"
-  },
-  "widgets": {
-   "state": {},
-   "version": "1.1.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 1
-}