137 lines
2.7 KiB
Plaintext
137 lines
2.7 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"In this exercise, we'll do calculations on many numbers at once. Python provides the numpy library for that."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# !pip install numpy"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"\n",
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"%matplotlib notebook\n",
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"from matplotlib import pyplot"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Exercise:** Use `np.arange(..., ...)` to create a vector from `0` up to and including `5`."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"x = None\n",
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"\n",
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"print('x: ', x)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Exercise:** Extract `1` from all the numbers"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"y = None\n",
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"print('y: ', y)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Exercise:** Take the square root of all these numbers, either using `** 0.5` or `np.sqrt( ... )`"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"y = None\n",
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"print('y: ', y)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Notice that the square root of `-1` is not defined, and hence the result is *not a number* (nan).\n",
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"\n",
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"The cell below will make a plot of `x` and `y`."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"pyplot.plot(x, y)\n",
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"pyplot.xlabel('x')\n",
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"pyplot.ylabel('y')\n",
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"None"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"You have learned to use `numpy` for so called vector operations, these are mathematical operations on many numbers as well. This field is called *linear algebra*, and is a usefull field on its own, in particular often used in artificial intelligence."
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]
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}
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],
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"metadata": {
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"hide_input": false,
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.4.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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