Creating a Series

Json/Converting_Python_object_containing_all_the_legal_data_types.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "authorship_tag": "ABX9TyNGSJJ+iuyj5ZBob0JkgoG6",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/amithbiju/FlutterChatAppTutorial/blob/master/Json/Converting_Python_object_containing_all_the_legal_data_types.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "6LrSXims3jdj",
+        "outputId": "88eaf273-3b87-4bb0-a59f-599b073b6780"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "{\"name\": \"John\", \"age\": 30, \"married\": true, \"divorced\": false, \"children\": [\"Ann\", \"Billy\"], \"pets\": null, \"cars\": [{\"model\": \"BMW 230\", \"mpg\": 27.5}, {\"model\": \"Ford Edge\", \"mpg\": 24.1}]}\n"
+          ]
+        }
+      ],
+      "source": [
+        "import json\n",
+        "\n",
+        "x = {\n",
+        "  \"name\": \"John\",\n",
+        "  \"age\": 30,\n",
+        "  \"married\": True,\n",
+        "  \"divorced\": False,\n",
+        "  \"children\": (\"Ann\",\"Billy\"),\n",
+        "  \"pets\": None,\n",
+        "  \"cars\": [\n",
+        "    {\"model\": \"BMW 230\", \"mpg\": 27.5},\n",
+        "    {\"model\": \"Ford Edge\", \"mpg\": 24.1}\n",
+        "  ]\n",
+        "}\n",
+        "\n",
+        "print(json.dumps(x))\n"
+      ]
+    }
+  ]
+}

PyTorch_Tensors_to_fit_a_third_order_polynomial_to_sine_function_.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "authorship_tag": "ABX9TyMt56DabNBLu2zfWbH6oeH9",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/amithbiju/FlutterChatAppTutorial/blob/master/PyTorch_Tensors_to_fit_a_third_order_polynomial_to_sine_function_.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "ntcctNbd5zG8"
+      },
+      "outputs": [],
+      "source": [
+        "import torch\n",
+        "import math\n",
+        "\n",
+        "\n",
+        "dtype = torch.float\n",
+        "device = torch.device(\"cpu\")\n",
+        "# device = torch.device(\"cuda:0\") # Uncomment this to run on GPU\n",
+        "\n",
+        "# Create random input and output data\n",
+        "x = torch.linspace(-math.pi, math.pi, 2000, device=device, dtype=dtype)\n",
+        "y = torch.sin(x)\n",
+        "\n",
+        "# Randomly initialize weights\n",
+        "a = torch.randn((), device=device, dtype=dtype)\n",
+        "b = torch.randn((), device=device, dtype=dtype)\n",
+        "c = torch.randn((), device=device, dtype=dtype)\n",
+        "d = torch.randn((), device=device, dtype=dtype)\n",
+        "\n",
+        "learning_rate = 1e-6\n",
+        "for t in range(2000):\n",
+        "    # Forward pass: compute predicted y\n",
+        "    y_pred = a + b * x + c * x ** 2 + d * x ** 3\n",
+        "\n",
+        "    # Compute and print loss\n",
+        "    loss = (y_pred - y).pow(2).sum().item()\n",
+        "    if t % 100 == 99:\n",
+        "        print(t, loss)\n",
+        "\n",
+        "    # Backprop to compute gradients of a, b, c, d with respect to loss\n",
+        "    grad_y_pred = 2.0 * (y_pred - y)\n",
+        "    grad_a = grad_y_pred.sum()\n",
+        "    grad_b = (grad_y_pred * x).sum()\n",
+        "    grad_c = (grad_y_pred * x ** 2).sum()\n",
+        "    grad_d = (grad_y_pred * x ** 3).sum()\n",
+        "\n",
+        "    # Update weights using gradient descent\n",
+        "    a -= learning_rate * grad_a\n",
+        "    b -= learning_rate * grad_b\n",
+        "    c -= learning_rate * grad_c\n",
+        "    d -= learning_rate * grad_d\n",
+        "\n",
+        "\n",
+        "print(f'Result: y = {a.item()} + {b.item()} x + {c.item()} x^2 + {d.item()} x^3')"
+      ]
+    }
+  ]
+}

Untitled0.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "authorship_tag": "ABX9TyPc0lLR8A+7DCW7vCUNzoU2",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/amithbiju/FlutterChatAppTutorial/blob/master/Untitled0.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "J25Ag0V0meLA",
+        "outputId": "6d2d1ddf-096e-4a83-c3d2-7a3bcc98c085"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "amith\n"
+          ]
+        }
+      ],
+      "source": [
+        "print(\"amith\")"
+      ]
+    }
+  ]
+}

pandas/Creating_a_Series.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "authorship_tag": "ABX9TyMyBMyDx1JS0lDsmFXmj/Lp",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/amithbiju/FlutterChatAppTutorial/blob/vr_1/pandas/Creating_a_Series.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "EGmbg4gohOKp",
+        "outputId": "7a992dd9-2a44-4ac1-f4fb-06a3c5059c28"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
+            "Requirement already satisfied: pandas in /usr/local/lib/python3.8/dist-packages (1.3.5)\n",
+            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas) (2022.6)\n",
+            "Requirement already satisfied: numpy>=1.17.3 in /usr/local/lib/python3.8/dist-packages (from pandas) (1.21.6)\n",
+            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas) (2.8.2)\n",
+            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.8/dist-packages (from python-dateutil>=2.7.3->pandas) (1.15.0)\n"
+          ]
+        }
+      ],
+      "source": [
+        "! pip install pandas"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import pandas as pd\n",
+        "import numpy as np\n",
+        "\n",
+        "\n",
+        "# Creating empty series\n",
+        "ser = pd.Series()\n",
+        "\n",
+        "print(ser)\n",
+        "\n",
+        "# simple array\n",
+        "data = np.array(['g', 'e', 'e', 'k', 's'])\n",
+        "\n",
+        "ser = pd.Series(data)\n",
+        "print(ser)\n"
+      ],
+      "metadata": {
+        "id": "gTCNVZiCj31S"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}

skiPy/Double_Integrals.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "authorship_tag": "ABX9TyPoOxZlKRHjQLzp5Z472l3B",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/amithbiju/FlutterChatAppTutorial/blob/master/skiPy/Double_Integrals.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "-yhh9MOSLk0G",
+        "outputId": "1d7ab912-5f54-4cff-d0bc-952e91bc0923"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
+            "Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (1.7.3)\n",
+            "Requirement already satisfied: numpy<1.23.0,>=1.16.5 in /usr/local/lib/python3.8/dist-packages (from scipy) (1.21.6)\n"
+          ]
+        }
+      ],
+      "source": [
+        "! pip install scipy"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from scipy import integrate\n",
+        "import numpy as np\n",
+        "f = lambda y, x: x*y**2\n",
+        "i = integrate.dblquad(f, 0, 2, lambda x: 0, lambda x: 1)\n",
+        "# print the results\n",
+        "print(i)\n"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "_dSQfyOCMhVw",
+        "outputId": "223896e0-c130-4152-8333-e0590fcfa02f"
+      },
+      "execution_count": 4,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "(0.6666666666666667, 7.401486830834377e-15)\n"
+          ]
+        }
+      ]
+    }
+  ]
+}