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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# **Task 1**\n",
+        "\n",
+        "Your goal is to find the answer of the dot product of the matrices of sizes (2,3), (3,5), (5,2) and (3,3).\n",
+        "\n",
+        "## **Workflow:**\n",
+        "1. Define the matrices of given sizes.\n",
+        "2. Print the matrices.\n",
+        "3. Use the np.dot function.\n",
+        "4. Print the output at each step.\n",
+        "5. Print the result.\n",
+        "\n",
+        "(Print the shape of matrix always with the matrix)\n"
+      ],
+      "metadata": {
+        "id": "6LkPygla_OXh"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# Import Numpy\n",
+        "import numpy as np"
+      ],
+      "metadata": {
+        "id": "Z8iSVv-r_WkT"
+      },
+      "execution_count": 3,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# Define the 4 matrices as A,B,C,D\n",
+        "A= np.random.randint(1, 10, size=(2, 3))\n",
+        "B= np.random.randint(1, 10, size=(3, 5))\n",
+        "C= np.random.randint(1, 10, size=(5, 2))\n",
+        "D= np.random.randint(1, 10, size=(3, 3))"
+      ],
+      "metadata": {
+        "id": "r1pVl7LbA1_I"
+      },
+      "execution_count": 11,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# Print the 4 matrices\n",
+        "print(A)\n",
+        "print(B)\n",
+        "print(C)\n",
+        "print(D)"
+      ],
+      "metadata": {
+        "id": "uJHj_CbhA83b",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "f4b9108c-aa46-4629-94d9-ee474dafe095"
+      },
+      "execution_count": 12,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[[2 7 3]\n",
+            " [2 7 4]]\n",
+            "[[7 6 3 2 7]\n",
+            " [9 8 2 5 3]\n",
+            " [8 2 6 2 8]]\n",
+            "[[9 1]\n",
+            " [2 7]\n",
+            " [7 1]\n",
+            " [3 5]\n",
+            " [3 6]]\n",
+            "[[9 9 6]\n",
+            " [2 3 9]\n",
+            " [4 7 5]]\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# Find the Dot Product of matrices\n",
+        "m = np.dot(A,D)\n",
+        "n = np.dot(m,B)\n",
+        "o = np.dot(n,C)"
+      ],
+      "metadata": {
+        "id": "MDcD7tOWBMzG"
+      },
+      "execution_count": 17,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# ValueError: shapes (2,2) and (3,3) not aligned: 2 (dim 1) != 3 (dim 0)\n",
+        "\n",
+        "Now the task is to define a function named is_compatible() that takes 2 matrices as input and only allows the dot product if the condition number of **columns** in the first matrix (A) matches the number of **rows** in the second matrix (B).\n",
+        "\n",
+        "Print the ouput if condition is satisfied\n",
+        "Else print \"Dimension Error!!\"\n",
+        "\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "Rv1D09dyB0eP"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "def is_compatible(A, B):\n",
+        "  pass"
+      ],
+      "metadata": {
+        "id": "RmS0xS8tCjNC"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# Find Dot product only if the matrices are compatible"
+      ],
+      "metadata": {
+        "id": "ds0XYSZ6E9nl"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# **Task 2**\n",
+        "\n",
+        "Your goal is to define a function that simulates a number-guessing game called \"Up-Down.\" The function, named up_down, should take an integer rounds as input, representing the number of turns the player gets.\n",
+        "\n",
+        "Game Rules:\n",
+        "\n",
+        "1. The player inputs a number between 1 and 12 for each round.\n",
+        "2. The computer randomly selects a number between 1 and 12.\n",
+        "3. The scoring system is as follows:\n",
+        "  \n",
+        "  a. If computer's guess is less than 7 and the player gains points equivalent to their guess if their guess is also less than 7, otherwise, they lose points equivalent to their guess.\n",
+        "  \n",
+        "  b. If computer's guess is exactly 7, the player gains 14 points if thier guess is 7, otherwise, they lose points equivalent to their guess.\n",
+        "  \n",
+        "  c. If computer's guess is greater than 7 and the player gains points equivalent to their guess if their guess is also greater than 7, otherwise, they lose points equivalent to their guess.\n",
+        "\n",
+        "4. The game continues until:\n",
+        "\n",
+        "  a. The player reaches more than 30 points, they win.\n",
+        "\n",
+        "  b. The player reaches less than -30 points, they lose.\n",
+        "\n",
+        "  c. The maximum number of rounds is reached.\n",
+        "  \n",
+        "At the end of the game, the function should print the final score.\n",
+        "\n",
+        "Your task is to implement this function in Python using the given rules."
+      ],
+      "metadata": {
+        "id": "SR_JeHeEdWOX"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "def up_down(rounds):\n",
+        "  pass"
+      ],
+      "metadata": {
+        "id": "0fxnUDma7aPx"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}
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