deploy: c4c03c8

Author: mmcky

_admonition/gpu.html

@@ -2,7 +2,7 @@
  "cells": [
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+   "id": "b3053a29",
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    "source": [
     "\n",
@@ -19,7 +19,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6d4310c5",
+   "id": "13c10839",
    "metadata": {},
    "source": [
     "# About These Lectures\n",
@@ -31,7 +31,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fc2c2316",
+   "id": "8e56ad76",
    "metadata": {},
    "source": [
     "## Overview\n",
@@ -55,7 +55,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a3aae76e",
+   "id": "c4b8f380",
    "metadata": {},
    "source": [
     "### Can’t I Just Use LLMs?\n",
@@ -79,7 +79,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e90aef03",
+   "id": "faffd209",
    "metadata": {},
    "source": [
     "### Isn’t MATLAB Better?\n",
@@ -102,7 +102,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bbed3bd9",
+   "id": "d4ae20cf",
    "metadata": {},
    "source": [
     "## Introducing Python\n",
@@ -120,7 +120,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a0bb1669",
+   "id": "e381293e",
    "metadata": {},
    "source": [
     "### Common Uses\n",
@@ -152,7 +152,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c9ec9647",
+   "id": "210e58ee",
    "metadata": {},
    "source": [
     "### Relative Popularity\n",
@@ -175,7 +175,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "409d94da",
+   "id": "4246ddc3",
    "metadata": {},
    "source": [
     "### Features\n",
@@ -193,7 +193,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "65516ab2",
+   "id": "d91b61cc",
    "metadata": {},
    "source": [
     "### Syntax and Design\n",
@@ -211,7 +211,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d01f108e",
+   "id": "bbefa921",
    "metadata": {
     "hide-output": false
    },
@@ -269,7 +269,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "918c8976",
+   "id": "fc60637f",
    "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": "48487e62",
+   "id": "72237d88",
    "metadata": {
     "hide-output": false
    },
@@ -305,7 +305,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "338dd6cc",
+   "id": "44eb0e8c",
    "metadata": {},
    "source": [
     "### The AI Connection\n",
@@ -327,7 +327,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8f279729",
+   "id": "c09c23de",
    "metadata": {},
    "source": [
     "## Scientific Programming with Python\n",
@@ -354,7 +354,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "394702eb",
+   "id": "c7b9ccc1",
    "metadata": {},
    "source": [
     "### NumPy\n",
@@ -371,7 +371,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "80e8d47b",
+   "id": "f582f9c7",
    "metadata": {
     "hide-output": false
    },
@@ -383,7 +383,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b2e5e79a",
+   "id": "431a378e",
    "metadata": {},
    "source": [
     "This array is very small so it’s fine to work with pure Python.\n",
@@ -401,7 +401,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b7b6d553",
+   "id": "c50a9b72",
    "metadata": {
     "hide-output": false
    },
@@ -415,7 +415,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "acb6287c",
+   "id": "26a882a0",
    "metadata": {},
    "source": [
     "Now let’s transform this array by applying functions to it."
@@ -424,7 +424,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "7812d408",
+   "id": "a35aee9c",
    "metadata": {
     "hide-output": false
    },
@@ -436,7 +436,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f014cf5b",
+   "id": "be12cc03",
    "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": "c96d19b8",
+   "id": "4c7ca39b",
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@@ -456,7 +456,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "85d83535",
+   "id": "c1188dd0",
    "metadata": {},
    "source": [
     "We can also do many other tasks, like\n",
@@ -471,7 +471,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0f688edf",
+   "id": "a43ef855",
    "metadata": {},
    "source": [
     "### NumPy Alternatives\n",
@@ -497,7 +497,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cc6acdeb",
+   "id": "af2f41a4",
    "metadata": {},
    "source": [
     "### SciPy\n",
@@ -512,7 +512,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f07fc390",
+   "id": "d0838e7e",
    "metadata": {
     "hide-output": false
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@@ -528,7 +528,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "70dd4185",
+   "id": "3321678c",
    "metadata": {},
    "source": [
     "SciPy includes many of the standard routines used in\n",
@@ -548,7 +548,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "db9397a8",
+   "id": "ee1819b5",
    "metadata": {},
    "source": [
     "### Graphics\n",
@@ -594,7 +594,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2727864d",
+   "id": "bf380351",
    "metadata": {},
    "source": [
     "### Networks and Graphs\n",
@@ -628,7 +628,7 @@
   {
    "cell_type": "code",
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-   "id": "629cf2c1",
+   "id": "7969ad50",
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@@ -663,7 +663,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5d0b9350",
+   "id": "3e5ad0be",
    "metadata": {},
    "source": [
     "### Other Scientific Libraries\n",
@@ -698,7 +698,7 @@
   }
  ],
  "metadata": {
-  "date": 1764291148.4581158,
+  "date": 1764540625.83234,
   "filename": "about_py.md",
   "kernelspec": {
    "display_name": "Python",