mirror of
https://github.com/deepseek-ai/DeepSeek-Coder.git
synced 2025-02-23 06:09:07 -05:00
Created using Colab
This commit is contained in:
Orrm23
parent
4ef0af1a7f
commit
3949954973
@ -92,7 +92,7 @@
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"base_uri": "https://localhost:8080/"
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},
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"id": "_x9QzbrMOl0l",
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"outputId": "9750543d-bfea-4451-a95c-4a6cfcc2e0ba"
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"outputId": "ab81e859-9cc0-4483-c174-5012b2b47ca4"
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},
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"source": [
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"print(dataset.data)\n",
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@ -283,7 +283,7 @@
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"height": 424
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},
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"id": "EG1_3L0hOoq0",
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"outputId": "464b4950-8a29-4131-8500-6bdacd714e32"
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"outputId": "4497898b-6264-4286-abb3-6394ec005754"
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},
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"source": [
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"X = pd.DataFrame(dataset.data, columns=dataset.feature_names)\n",
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@ -312,7 +312,7 @@
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],
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"text/html": [
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"\n",
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" <div id=\"df-389f57ea-0bd7-462a-9a96-b6a7dee9a497\" class=\"colab-df-container\">\n",
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" <div id=\"df-e2b913d5-fa21-4bb1-8f04-5952f668df8e\" class=\"colab-df-container\">\n",
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" <div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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@ -422,7 +422,7 @@
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" <div class=\"colab-df-buttons\">\n",
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"\n",
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" <div class=\"colab-df-container\">\n",
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" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-389f57ea-0bd7-462a-9a96-b6a7dee9a497')\"\n",
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" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e2b913d5-fa21-4bb1-8f04-5952f668df8e')\"\n",
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" title=\"Convert this dataframe to an interactive table.\"\n",
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" style=\"display:none;\">\n",
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"\n",
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@ -474,12 +474,12 @@
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"\n",
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" <script>\n",
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" const buttonEl =\n",
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" document.querySelector('#df-389f57ea-0bd7-462a-9a96-b6a7dee9a497 button.colab-df-convert');\n",
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" document.querySelector('#df-e2b913d5-fa21-4bb1-8f04-5952f668df8e button.colab-df-convert');\n",
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" buttonEl.style.display =\n",
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" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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"\n",
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" async function convertToInteractive(key) {\n",
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" const element = document.querySelector('#df-389f57ea-0bd7-462a-9a96-b6a7dee9a497');\n",
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" const element = document.querySelector('#df-e2b913d5-fa21-4bb1-8f04-5952f668df8e');\n",
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" const dataTable =\n",
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" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
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" [key], {});\n",
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@ -499,8 +499,8 @@
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" </div>\n",
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"\n",
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"\n",
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"<div id=\"df-30a8233c-6cf9-497b-a5cb-cb33cb614e4c\">\n",
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" <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-30a8233c-6cf9-497b-a5cb-cb33cb614e4c')\"\n",
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"<div id=\"df-3fa5a8c8-0d89-4e94-9eb6-a6f83fb4b61a\">\n",
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" <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-3fa5a8c8-0d89-4e94-9eb6-a6f83fb4b61a')\"\n",
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" title=\"Suggest charts\"\n",
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" style=\"display:none;\">\n",
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"\n",
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@ -619,14 +619,14 @@
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" }\n",
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" (() => {\n",
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" let quickchartButtonEl =\n",
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" document.querySelector('#df-30a8233c-6cf9-497b-a5cb-cb33cb614e4c button');\n",
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" document.querySelector('#df-3fa5a8c8-0d89-4e94-9eb6-a6f83fb4b61a button');\n",
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" quickchartButtonEl.style.display =\n",
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" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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" })();\n",
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" </script>\n",
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"</div>\n",
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"\n",
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" <div id=\"id_4f5a864a-1903-4cf2-963b-999ead609f73\">\n",
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" <div id=\"id_cd5c8bd3-0029-41c9-854f-eed3f438d4f0\">\n",
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" <style>\n",
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" .colab-df-generate {\n",
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" background-color: #E8F0FE;\n",
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@ -670,7 +670,7 @@
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" <script>\n",
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" (() => {\n",
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" const buttonEl =\n",
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" document.querySelector('#id_4f5a864a-1903-4cf2-963b-999ead609f73 button.colab-df-generate');\n",
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" document.querySelector('#id_cd5c8bd3-0029-41c9-854f-eed3f438d4f0 button.colab-df-generate');\n",
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" buttonEl.style.display =\n",
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" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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"\n",
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@ -702,7 +702,7 @@
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"base_uri": "https://localhost:8080/"
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},
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"id": "fVIBC6zbPmD_",
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"outputId": "729cc236-51a5-4704-8002-a5326bc1d1ab"
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"outputId": "1a834214-4d26-4413-da1f-2a5a9a45b115"
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},
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"source": [
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"Y = dataset.target\n",
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@ -744,7 +744,7 @@
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"base_uri": "https://localhost:8080/"
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},
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"id": "WsXx-qmhPzSV",
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"outputId": "78fe0df9-ffdb-4fd2-9d96-52b8d2ba36af"
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"outputId": "3234893f-95d4-477f-fa50-86e38ad8e391"
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},
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"source": [
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"from sklearn.model_selection import train_test_split\n",
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@ -781,7 +781,7 @@
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"height": 581
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},
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"id": "MLko_TEoSOVY",
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"outputId": "e9e13eb1-08fa-494c-f75d-0d9321bae504"
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"outputId": "932213ba-06aa-49c7-dbba-2ea593edf2d4"
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},
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"source": [
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"accuracy = []\n",
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@ -844,7 +844,7 @@
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"height": 80
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},
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"id": "_1iHKy-0QHm6",
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"outputId": "8a7a3030-1d60-4018-f225-5c2e65fdbe9a"
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"outputId": "63f5d1c9-bef7-4778-9a1f-8f2170a90770"
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},
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"source": [
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"from sklearn.tree import DecisionTreeClassifier\n",
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@ -1299,7 +1299,7 @@
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"base_uri": "https://localhost:8080/"
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},
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"id": "H9IXzjDeXFfv",
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"outputId": "8600174d-43a0-49fd-d3fd-3b312e858210"
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"outputId": "0b2faac8-d1d8-4326-eed2-adca7901bbf1"
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},
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"source": [
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"y_pred = model.predict(X_test)\n",
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@ -1369,7 +1369,7 @@
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"base_uri": "https://localhost:8080/"
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},
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"id": "z6zi5kA4XjXx",
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"outputId": "0a1dde70-cc96-4e28-a503-64f5e5272ba7"
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"outputId": "93e85e20-69e0-4772-deb5-2e6092cb6940"
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},
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"source": [
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"from sklearn.metrics import accuracy_score\n",
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