mirror of
https://github.com/ArthurDanjou/ml_exercises.git
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81 lines
2.6 KiB
Plaintext
Executable File
81 lines
2.6 KiB
Plaintext
Executable File
{
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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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"# Test if installation was successful"
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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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"# check versions of the libraries\n",
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"# they should not be too much behind the ones in the comments...\n",
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"import numpy\n",
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"print(\"numpy\", numpy.__version__) # >= 1.22.3\n",
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"import pandas\n",
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"print(\"pandas\", pandas.__version__) # >= 1.4.2\n",
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"import scipy\n",
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"print(\"scipy\", scipy.__version__) # >= 1.8.0\n",
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"import sklearn\n",
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"print(\"sklearn\", sklearn.__version__) # >= 1.1.2\n",
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"import matplotlib\n",
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"print(\"matplotlib\", matplotlib.__version__) # >= 3.5.1\n",
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"import PIL\n",
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"print(\"pillow\", PIL.__version__) # >= 9.1.0\n",
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"import plotly\n",
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"print(\"plotly\", plotly.__version__) # >= 5.7.0\n",
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"import xlrd\n",
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"print(\"xlrd\", xlrd.__version__) # >= 2.0.1\n",
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"print(\"Congratulations! Your installation of the basic libraries was successful!\")\n",
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"# the following libraries are needed for the neural network example \n",
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"# (if you're working with the recommended pytorch, not keras/tensorflow)\n",
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"# if you have a computer with a (CUDA-enabled Nvidia) GPU, checkout this site:\n",
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"# https://pytorch.org/get-started/locally/\n",
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"# to install the correct version that can utilize the capabilities of your GPU\n",
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"# (if you're working on a normal laptop and you don't know what GPU means,\n",
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"# don't worry about it and just execute `$ pip install torch torchvision skorch`)\n",
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"import torch\n",
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"print(\"torch\", torch.__version__) # >= 1.12.1\n",
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"import torchvision\n",
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"print(\"torchvision\", torchvision.__version__) # >= 0.13.1\n",
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"import skorch\n",
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"print(\"skorch\", skorch.__version__) # >= 0.11.0\n",
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"print(\"Congratulations! Your installation of the neural network libraries was successful!\")"
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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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}
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],
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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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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},
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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": "3.10.2"
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"nbformat": 4,
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