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  1. {
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  3. {
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  6. "source": [
  7. "# Python & Machine Learning Exercises"
  8. ]
  9. },
  10. {
  11. "cell_type": "markdown",
  12. "metadata": {},
  13. "source": [
  14. "## Python\n",
  15. "\n",
  16. "### (1)字符串\n",
  17. "给定一个文章,找出每个单词的出现次数\n",
  18. "\n",
  19. "```\n",
  20. "One is always on a strange road, watching strange scenery and listening to strange music. Then one day, you will find that the things you try hard to forget are already gone. \n",
  21. "```\n",
  22. "\n",
  23. "### (2)组合\n",
  24. "有 1、2、3、4 个数字,能组成多少个互不相同且无重复数字的三位数?都是多少?\n",
  25. "\n",
  26. "\n",
  27. "### (3) 判断\n",
  28. "企业发放的奖金根据利润提成。利润(I): \n",
  29. "* 低于或等于 10 万元时,奖金可提 10%; \n",
  30. "* 高于 10 万元,低于 20 万元时,低于 10 万元的部分按 10%提成,高于 10 万元的部分,可提成 7.5%; \n",
  31. "* 20 万到 40 万之间时,高于 20 万元的部分,可提成 5%; \n",
  32. "* 40 万到 60 万之间时,高于 40 万元的部分,可提成 3%; \n",
  33. "* 60 万到 100 万之间时,高于 60 万元的部分,可提成 1.5%, \n",
  34. "* 高于 100 万元时, 超过 100 万元的部分按 1%提成, \n",
  35. "从键盘输入当月利润 I,求应发放奖金总数?\n",
  36. "\n",
  37. "### (4)循环\n",
  38. "输出9x9的乘法口诀表\n",
  39. "\n",
  40. "### (5)算法\n",
  41. "给一个数字列表,将其按照由大到小的顺序排列\n",
  42. "\n",
  43. "例如\n",
  44. "```\n",
  45. "1, 10, 4, 2, 9, 2, 34, 5, 9, 8, 5, 0\n",
  46. "```\n",
  47. "\n",
  48. "### (6)应用1\n",
  49. "做为 Apple Store App 独立开发者,你要搞限时促销,为你的应用生成激活码(或者优惠券),使用 Python 如何生成 200 个激活码(或者优惠券)?\n",
  50. "\n",
  51. "需要考虑什么是激活码?有什么特性?例如`KR603guyVvR`是一个激活码\n",
  52. "\n",
  53. "### (7)应用2\n",
  54. "需要把某个目录下面所有的某种类型的文件找到。\n",
  55. "例如把`c:`下面所有的`.dll`文件找到\n",
  56. "\n",
  57. "### (8)应用3\n",
  58. "你有个目录,里面是程序(假如是C或者是Python),统计一下你写过多少行代码。包括空行和注释,但是要分别列出来。\n",
  59. "\n"
  60. ]
  61. },
  62. {
  63. "cell_type": "markdown",
  64. "metadata": {},
  65. "source": [
  66. "## 数值计算\n",
  67. "\n",
  68. "\n",
  69. "### (1)对于一个存在在数组,如何添加一个用0填充的边界?\n",
  70. "例如对一个二维矩阵\n",
  71. "```\n",
  72. "10, 34, 54, 23\n",
  73. "31, 87, 53, 68\n",
  74. "98, 49, 25, 11\n",
  75. "84, 32, 67, 88\n",
  76. "```\n",
  77. "\n",
  78. "变换成\n",
  79. "```\n",
  80. " 0, 0, 0, 0, 0, 0\n",
  81. " 0, 10, 34, 54, 23, 0\n",
  82. " 0, 31, 87, 53, 68, 0\n",
  83. " 0, 98, 49, 25, 11, 0\n",
  84. " 0, 84, 32, 67, 88, 0\n",
  85. " 0, 0, 0, 0, 0, 0\n",
  86. "```\n",
  87. "\n",
  88. "### (2) 创建一个 5x5的矩阵,并设置值1,2,3,4落在其对角线下方位置\n",
  89. "\n",
  90. "\n",
  91. "### (3) 创建一个8x8 的矩阵,并且设置成棋盘样式\n",
  92. "\n",
  93. "\n",
  94. "### (4)求解线性方程组\n",
  95. "\n",
  96. "给定一个方程组,如何求出其的方程解。有多种方法,分析各种方法的优缺点(最简单的方式是消元方)。\n",
  97. "\n",
  98. "例如\n",
  99. "```\n",
  100. "3x + 4y + 2z = 10\n",
  101. "5x + 3y + 4z = 14\n",
  102. "8x + 2y + 7z = 20\n",
  103. "```\n",
  104. "\n",
  105. "编程写出求解的程序\n"
  106. ]
  107. },
  108. {
  109. "cell_type": "code",
  110. "execution_count": null,
  111. "metadata": {},
  112. "outputs": [],
  113. "source": []
  114. }
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  116. "metadata": {
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  118. "display_name": "Python 3",
  119. "language": "python",
  120. "name": "python3"
  121. },
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  125. "version": 3
  126. },
  127. "file_extension": ".py",
  128. "mimetype": "text/x-python",
  129. "name": "python",
  130. "nbconvert_exporter": "python",
  131. "pygments_lexer": "ipython3",
  132. "version": "3.5.2"
  133. }
  134. },
  135. "nbformat": 4,
  136. "nbformat_minor": 2
  137. }

机器学习越来越多应用到飞行器、机器人等领域,其目的是利用计算机实现类似人类的智能,从而实现装备的智能化与无人化。本课程旨在引导学生掌握机器学习的基本知识、典型方法与技术,通过具体的应用案例激发学生对该学科的兴趣,鼓励学生能够从人工智能的角度来分析、解决飞行器、机器人所面临的问题和挑战。本课程主要内容包括Python编程基础,机器学习模型,无监督学习、监督学习、深度学习基础知识与实现,并学习如何利用机器学习解决实际问题,从而全面提升自我的《综合能力》。

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