{ "cells": [ { "cell_type": "markdown", "id": "7cac0fb8", "metadata": { "origin_pos": 0 }, "source": [ "# Preliminaries\n", ":label:`chap_preliminaries`\n", "\n", "To prepare for your dive into deep learning,\n", "you will need a few survival skills:\n", "(i) techniques for storing and manipulating data;\n", "(ii) libraries for ingesting \n", "and preprocessing data from a variety of sources;\n", "(iii) knowledge of the basic linear algebraic operations\n", "that we apply to high-dimensional data elements;\n", "(iv) just enough calculus to determine\n", "which direction to adjust each parameter\n", "in order to decrease the loss function;\n", "(v) the ability to automatically compute derivatives\n", "so that you can forget much of \n", "the calculus you just learned;\n", "(vi) some basic fluency in probability,\n", "our primary language for reasoning under uncertainty;\n", "and (vii) some aptitude for finding answers \n", "in the official documentation when you get stuck.\n", "\n", "In short, this chapter provides a rapid introduction \n", "to the basics that you will need to follow \n", "*most* of the technical content in this book.\n", "\n", ":begin_tab:toc\n", " - [ndarray](ndarray.ipynb)\n", " - [pandas](pandas.ipynb)\n", " - [linear-algebra](linear-algebra.ipynb)\n", " - [calculus](calculus.ipynb)\n", " - [autograd](autograd.ipynb)\n", " - [probability](probability.ipynb)\n", " - [lookup-api](lookup-api.ipynb)\n", ":end_tab:\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.9.23" }, "required_libs": [] }, "nbformat": 4, "nbformat_minor": 5 }