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[attr]lfs-file filter=lfs diff=lfs merge=lfs -text
*.pdf lfs-file

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.venv
.vscode

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3.12

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "129d4b8c",
"metadata": {},
"outputs": [],
"source": [
"import numpy\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "markdown",
"id": "d35579ac",
"metadata": {},
"source": [
"# Study of algorithm\n",
"\n",
"* Improve Performance, $P$\n",
"* At some Task, $T$\n",
"* With Experience, $E$\n",
"\n",
"Learning: **Improving $P$ at $T$ with $E$**\n",
"\n",
"* $T$: Output\n",
"* $E$: Training Data\n",
"* $P$: Target (or Loss) function\n",
" * If you cannot measure it, you cannot improve it - Kelvin\n",
" * e.g.: Error rate, Euclidean distance, Logproba, Information theoretical measures(Mutual information, KL)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0d742636",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "255ea9b1",
"metadata": {},
"source": [
"# Derivation w.r.t Matrix\n",
"\n",
"In the typical $f: \\R \\to \\R$\n",
"$$f(x) = ax, \\quad df/dx = a$$\n",
"and\n",
"\n",
"$$f(x) = x^2, \\quad df/dx = 2x$$\n",
"\n",
"\n",
"By the way, $f = w^Tx,\\, (w \\in \\R^D, x\\in \\R^D)$\n",
"\n",
"$$\\frac{df}{dx} = \\frac{\\partial f}{\\partial x_1}$$\n",
"\n",
"\n",
"In the case $f(x) = x^2 = x^Tx$\n",
"\n",
"$$\\frac{df}{dx} = 2x$$\n",
"\n",
"for example: $f(x) = w^Tx$\n",
"\n",
"$$f(x) = \\sum w_i x_i$$\n",
"$$\\frac{\\partial f}{\\partial x_i} = w_i$$\n",
"$$\\therefore \\frac{d f}{d x} = w$$"
]
},
{
"cell_type": "markdown",
"id": "84468a76",
"metadata": {},
"source": [
"$tr[M] = \\sum^{D}_{i=1}{M_{ii}}$"
]
},
{
"cell_type": "markdown",
"id": "e8671c90",
"metadata": {},
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "2025-02-AI (3.12.11)",
"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": "3.12.11"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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def main():
print("Hello from 2025-02-ai!")
if __name__ == "__main__":
main()

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[project]
name = "2025-02-ai"
version = "0.1.0"
description = "Add your description here"
readme = "README.md"
requires-python = ">=3.12"
dependencies = [
"jupyter>=1.1.1",
"matplotlib>=3.10.6",
"numpy>=2.3.3",
]

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