deploy: 341ec14

Author: mmcky

.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 58751540f8e36d9bc3930cff3edafa9e
+config: e006c22a5a26fcb42101f827b641f2a6
 tags: 645f666f9bcd5a90fca523b33c5a78b7

_images/03b104d0303985c2619f708f9b0b013bfe5ef75f21539811fd421627d0770c3a.png

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "3e2c971d",
+   "id": "bccdc720",
    "metadata": {},
    "source": [
     "\n",
@@ -19,7 +19,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "971fb999",
+   "id": "22da50aa",
    "metadata": {},
    "source": [
     "# About These Lectures\n",
@@ -31,7 +31,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5901c54f",
+   "id": "641434b6",
    "metadata": {},
    "source": [
     "## Overview\n",
@@ -55,7 +55,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "29bf6bc0",
+   "id": "c29f395f",
    "metadata": {},
    "source": [
     "### Can’t I Just Use LLMs?\n",
@@ -79,7 +79,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fb3a5c5f",
+   "id": "463193b8",
    "metadata": {},
    "source": [
     "### Isn’t MATLAB Better?\n",
@@ -102,7 +102,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7f03e393",
+   "id": "71fa4501",
    "metadata": {},
    "source": [
     "## Introducing Python\n",
@@ -120,7 +120,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "44965c89",
+   "id": "64ba0f87",
    "metadata": {},
    "source": [
     "### Common Uses\n",
@@ -152,7 +152,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c24661a2",
+   "id": "7d53dcb9",
    "metadata": {},
    "source": [
     "### Relative Popularity\n",
@@ -175,7 +175,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1df39b8e",
+   "id": "775ba724",
    "metadata": {},
    "source": [
     "### Features\n",
@@ -193,7 +193,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ed1b530a",
+   "id": "0d76993e",
    "metadata": {},
    "source": [
     "### Syntax and Design\n",
@@ -211,7 +211,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "affbed36",
+   "id": "71cf4983",
    "metadata": {
     "hide-output": false
    },
@@ -269,7 +269,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fd15b7cc",
+   "id": "ced3f595",
    "metadata": {},
    "source": [
     "This Java code opens an imaginary file called `data.csv` and computes the mean\n",
@@ -283,7 +283,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "105e0f19",
+   "id": "873c4b4e",
    "metadata": {
     "hide-output": false
    },
@@ -305,7 +305,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "18a6780f",
+   "id": "e2c5c88f",
    "metadata": {},
    "source": [
     "### The AI Connection\n",
@@ -327,7 +327,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c26027ac",
+   "id": "061134e9",
    "metadata": {},
    "source": [
     "## Scientific Programming with Python\n",
@@ -354,7 +354,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5e47162e",
+   "id": "2f5503f7",
    "metadata": {},
    "source": [
     "### NumPy\n",
@@ -371,7 +371,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "bda364c9",
+   "id": "fa1bae38",
    "metadata": {
     "hide-output": false
    },
@@ -383,7 +383,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d6c313d0",
+   "id": "f0366d3b",
    "metadata": {},
    "source": [
     "This array is very small so it’s fine to work with pure Python.\n",
@@ -393,15 +393,15 @@
     "For this we need to use libraries for working with arrays.\n",
     "\n",
     "For Python, the most important matrix and array processing library is\n",
-    "[NumPy](https://www.numpy.org/) library.\n",
+    "[NumPy](https://numpy.org/) library.\n",
     "\n",
     "For example, let’s build a NumPy array with 100 elements"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "c956f0af",
+   "id": "2eea9a64",
    "metadata": {
     "hide-output": false
    },
@@ -415,7 +415,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9a9cf553",
+   "id": "3a5bc551",
    "metadata": {},
    "source": [
     "Now let’s transform this array by applying functions to it."
@@ -424,7 +424,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a4b5d512",
+   "id": "453f0473",
    "metadata": {
     "hide-output": false
    },
@@ -436,7 +436,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "64c9d73e",
+   "id": "32e7da1e",
    "metadata": {},
    "source": [
     "Now we can easily take the inner product of `b` and `c`."
@@ -445,7 +445,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "9e109f70",
+   "id": "55ec7c76",
    "metadata": {
     "hide-output": false
    },
@@ -456,7 +456,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d5cc8859",
+   "id": "d30ae172",
    "metadata": {},
    "source": [
     "We can also do many other tasks, like\n",
@@ -471,7 +471,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "57983fe5",
+   "id": "69e18595",
    "metadata": {},
    "source": [
     "### NumPy Alternatives\n",
@@ -497,12 +497,12 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c6f120f0",
+   "id": "308ba2d8",
    "metadata": {},
    "source": [
     "### SciPy\n",
     "\n",
-    "The [SciPy](https://www.scipy.org) library is built on top of NumPy and provides additional functionality.\n",
+    "The [SciPy](https://scipy.org/) library is built on top of NumPy and provides additional functionality.\n",
     "\n",
     "\n",
     "<a id='tuple-unpacking-example'></a>\n",
@@ -512,7 +512,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "1c86ba4a",
+   "id": "4bd7721c",
    "metadata": {
     "hide-output": false
    },
@@ -528,7 +528,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ca9e5693",
+   "id": "8b5b1059",
    "metadata": {},
    "source": [
     "SciPy includes many of the standard routines used in\n",
@@ -548,7 +548,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "904ce964",
+   "id": "6023eeba",
    "metadata": {},
    "source": [
     "### Graphics\n",
@@ -594,7 +594,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "61cd6440",
+   "id": "4450ddc5",
    "metadata": {},
    "source": [
     "### Networks and Graphs\n",
@@ -628,7 +628,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "147d60a1",
+   "id": "5d551c5b",
    "metadata": {
     "hide-output": false
    },
@@ -663,7 +663,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fbc87b65",
+   "id": "ff6f395e",
    "metadata": {},
    "source": [
     "### Other Scientific Libraries\n",
@@ -698,7 +698,7 @@
   }
  ],
  "metadata": {
-  "date": 1756348328.8648312,
+  "date": 1756362393.2715633,
   "filename": "about_py.md",
   "kernelspec": {
    "display_name": "Python",