Delete Stock.ipynb

Stock.ipynb

@@ -1,53 +0,0 @@
-{
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
-    "colab": {
-      "provenance": []
-    },
-    "kernelspec": {
-      "name": "python3",
-      "display_name": "Python 3"
-    },
-    "language_info": {
-      "name": "python"
-    }
-  },
-  "cells": [
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "6Pt_GlNEmvXv"
-      },
-      "outputs": [],
-      "source": [
-        "import joblib\n",
-        "import numpy as np\n",
-        "\n",
-        "\n",
-        "# Load your trained model\n",
-        "model = joblib.load('stock_model.pkl')\n",
-        "\n",
-        "# Define a function for prediction\n",
-        "def predict_stock_price(features):\n",
-        "    \"\"\"\n",
-        "    Predict stock price based on input features.\n",
-        "    :param features: Comma-separated string of numerical features\n",
-        "    :return: Predicted stock price\n",
-        "    \"\"\"\n",
-        "    try:\n",
-        "        # Convert input features from string to a numpy array\n",
-        "        features = np.array([float(x.strip()) for x in features.split(\",\")]).reshape(1, -1)\n",
-        "\n",
-        "        # Predict using the model\n",
-        "        prediction = model.predict(features)\n",
-        "        return f\"Predicted Stock Price: {prediction[0]}\"\n",
-        "    except ValueError:\n",
-        "        return \"Error: Please ensure all input features are numeric and comma-separated.\"\n",
-        "    except Exception as e:\n",
-        "        return f\"Error: {str(e)}\"\n"
-      ]
-    }
-  ]
-}