{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "```{admonition} Information\n", "__Section__: Introduction to image classification \n", "__Goal__: Understand a basic method to use images in machine learning experiments. \n", "__Time needed__: 70 min \n", "__Prerequisites__: Introduction about machine learning experiments\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Introduction to image classification" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this chapter, we will deal with image data. Before studying how image data quality can affect the results of a machine learning experiment, we need to understand how images are used in a machine learning experiments.\n", "\n", "There are many methods to use images in machine learning experiments, and we won't go through all of them as this would constitute a whole course in itself. In this course, we will only focus on a very simple method to use image data for classification." ] } ], "metadata": { "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": "3.7.1" }, "varInspector": { "cols": { "lenName": 16, "lenType": 16, "lenVar": 40 }, "kernels_config": { "python": { "delete_cmd_postfix": "", "delete_cmd_prefix": "del ", "library": "var_list.py", "varRefreshCmd": "print(var_dic_list())" }, "r": { "delete_cmd_postfix": ") ", "delete_cmd_prefix": "rm(", "library": "var_list.r", "varRefreshCmd": "cat(var_dic_list()) " } }, "types_to_exclude": [ "module", "function", "builtin_function_or_method", "instance", "_Feature" ], "window_display": false } }, "nbformat": 4, "nbformat_minor": 4 }