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  1. {
  2.  "cells": [
  3.   {
  4.    "cell_type": "code",
  5.    "execution_count": 2,
  6.    "metadata": {},
  7.    "outputs": [],
  8.    "source": [
  9.     "import numpy as np\n",
  10.     "A=np.array([[1,2],[3,4],[5,6],[7,8]])"
  11.    ]
  12.   },
  13.   {
  14.    "cell_type": "code",
  15.    "execution_count": 3,
  16.    "metadata": {},
  17.    "outputs": [
  18.     {
  19.      "data": {
  20.       "text/plain": [
  21.        "array([[1, 2],\n",
  22.        "       [3, 4],\n",
  23.        "       [5, 6],\n",
  24.        "       [7, 8]])"
  25.       ]
  26.      },
  27.      "execution_count": 3,
  28.      "metadata": {},
  29.      "output_type": "execute_result"
  30.     }
  31.    ],
  32.    "source": [
  33.     "A"
  34.    ]
  35.   },
  36.   {
  37.    "cell_type": "code",
  38.    "execution_count": 4,
  39.    "metadata": {},
  40.    "outputs": [],
  41.    "source": [
  42.     "B=np.array([[1,2,3],[4,5,6],[7,8,9]])"
  43.    ]
  44.   },
  45.   {
  46.    "cell_type": "code",
  47.    "execution_count": 5,
  48.    "metadata": {},
  49.    "outputs": [
  50.     {
  51.      "ename": "ValueError",
  52.      "evalue": "shapes (4,2) and (3,3) not aligned: 2 (dim 1) != 3 (dim 0)",
  53.      "output_type": "error",
  54.      "traceback": [
  55.       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
  56.       "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
  57.       "\u001b[0;32m<ipython-input-5-189f80e2c351>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mA\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mB\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
  58.       "\u001b[0;31mValueError\u001b[0m: shapes (4,2) and (3,3) not aligned: 2 (dim 1) != 3 (dim 0)"
  59.      ]
  60.     }
  61.    ],
  62.    "source": [
  63.     "np.dot(A,B)"
  64.    ]
  65.   },
  66.   {
  67.    "cell_type": "code",
  68.    "execution_count": null,
  69.    "metadata": {},
  70.    "outputs": [],
  71.    "source": []
  72.   }
  73.  ],
  74.  "metadata": {
  75.   "kernelspec": {
  76.    "display_name": "Python",
  77.    "language": "python",
  78.    "name": "conda-env-python-py"
  79.   },
  80.   "language_info": {
  81.    "codemirror_mode": {
  82.     "name": "ipython",
  83.     "version": 3
  84.    },
  85.    "file_extension": ".py",
  86.    "mimetype": "text/x-python",
  87.    "name": "python",
  88.    "nbconvert_exporter": "python",
  89.    "pygments_lexer": "ipython3",
  90.    "version": "3.6.7"
  91.   }
  92.  },
  93.  "nbformat": 4,
  94.  "nbformat_minor": 4
  95. }
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