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75 lines
1.6 KiB
75 lines
1.6 KiB
{
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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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"### Welcome to the world of Machine learning\n",
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"###### create the .venv environment form https://scikit-learn.org/stable/install.html\n",
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"###### use the .venv environment for the execution of the ipykernel\n",
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"###### first install scikit-learn, matplotlib, numpy, pandas, ipykernel in virtual environment"
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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": 7,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Shape: (2, 3, 4)\n",
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"3D Array: \n",
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" [[[ 1 2 3 4]\n",
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" [ 5 6 7 8]\n",
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" [ 9 10 11 12]]\n",
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"\n",
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" [[13 14 15 16]\n",
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" [17 18 19 20]\n",
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" [21 22 23 24]]]\n"
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]
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}
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],
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"source": [
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"import numpy as np\n",
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"a = np.array([\n",
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" [\n",
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" [1, 2, 3, 4],\n",
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" [5, 6, 7, 8],\n",
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" [9, 10, 11, 12]\n",
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" ],\n",
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" [\n",
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" [13, 14, 15, 16],\n",
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" [17, 18, 19, 20],\n",
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" [21, 22, 23, 24]\n",
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" ] \n",
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"])\n",
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"print(\"Shape:\", a.shape)\n",
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"print(\"3D Array: \\n\", a)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": ".venv",
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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": "3.13.3"
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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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