71 lines
1.7 KiB
Plaintext
71 lines
1.7 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "47153112-da26-4dbd-a32a-1abdd8bda4fa",
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"metadata": {
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"tags": []
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},
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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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"2949/2949 [==============================] - 1s 462us/step\n"
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]
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}
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],
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"source": [
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"import tensorflow as tf\n",
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"import pandas as pd\n",
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"import numpy as np\n",
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"import sklearn\n",
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"import sklearn.model_selection\n",
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"from tensorflow.keras.models import load_model\n",
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"\n",
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"feature_cols = ['year', 'mileage', 'vol_engine']\n",
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"\n",
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"model = load_model('model.h5')\n",
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"test_data = pd.read_csv('test.csv')\n",
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"\n",
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"predictions = model.predict(test_data[feature_cols])\n",
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"predicted_prices = [p[0] for p in predictions]\n",
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"\n",
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"\n",
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"results = pd.DataFrame({'id': test_data['id'], 'year': test_data['year'], 'mileage': test_data['mileage'], 'vol_engine': test_data['vol_engine'], 'predicted_price': predicted_prices})\n",
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"results.to_csv('predictions.csv', index=False)"
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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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"id": "bca76252-c90d-4343-8ff8-a665cd32cf26",
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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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"metadata": {
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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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"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": "3.11.2"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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