diff --git a/CM20315/CM20315_BackgroundMaths.ipynb b/CM20315/CM20315_BackgroundMaths.ipynb new file mode 100644 index 0000000..61151e8 --- /dev/null +++ b/CM20315/CM20315_BackgroundMaths.ipynb @@ -0,0 +1,105 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "provenance": [], + "authorship_tag": "ABX9TyP2uQebA3i1KuIqkrgmngWg", + "include_colab_link": true + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "language_info": { + "name": "python" + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "view-in-github", + "colab_type": "text" + }, + "source": [ + "\"Open" + ] + }, + { + "cell_type": "markdown", + "source": [ + "\n", + "# **CM20315 Background Mathematics**\n", + "\n", + "The purpose of this Python notebook is to make sure you can use CoLab and to familiarize yourself with some of the background mathematical concepts that you are going to need to understand deep learning.

It's not meant to be difficult and it may be that you know some or all of this information already.

Maths is *NOT* a spectator sport. You won't learn it by just listening to lectures or reading books. It really helps to interact with it and explore yourself.

Work through the cells below. In various places you will see the words **\"TO DO\"**. Follow the instructions at these places. If you can't figure out what is going on or how to complete the section, feel free to ask your fellow students or the TAs in the practical session or via Moodle. This does not count toward your final marks, but completeing it will help you do well in your coursework and exam and reduce your stress levels later on.\n" + ], + "metadata": { + "id": "s5zzKSOusPOB" + } + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "id": "aUAjBbqzivMY" + }, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "source": [ + "x = np.arange\n", + "\n", + "x = np.arange(0.01,10, 0.01)\n", + "y = np.log(x)\n", + "\n", + "\n", + "fig, ax = plt.subplots()\n", + "fig.set_size_inches(5.0,5.0, forward=True)\n", + "ax.plot(x,y,'r-')\n", + "ax.set_ylim([-5,3])\n", + "ax.set_xlim([0,10])\n", + "plt.savefig('Log.svg', format='svg')\n", + "plt.show" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 342 + }, + "id": "9WbDlaVksItZ", + "outputId": "66350910-8b3d-431b-cc3d-3e81f17b4a27" + }, + "execution_count": 2, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ] + }, + "metadata": {}, + "execution_count": 2 + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ] + } + ] +} \ No newline at end of file