[FreeCoursesOnline.Me] O'REILLY - Python for Data Science Complete Video Course Video Training

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  7. 01 - Python for Data Science Complete Video Course Video Training - Introduction.mp4 76.64MB
  8. 02 - Learning objectives.mp4 11.21MB
  9. 03 - 1.1 History of Python in data science.mp4 78.08MB
  10. 04 - 1.2 Overview of Python data science libraries.mp4 44.37MB
  11. 05 - 1.3 Future trends of Python in AI, ML, and data science.mp4 77.54MB
  12. 06 - Learning objectives.mp4 25.00MB
  13. 07 - 2.1 Create your first Colab document.mp4 328.82MB
  14. 08 - 2.2 Manage Colab documents.mp4 451.80MB
  15. 09 - 2.3 Use magic functions.mp4 156.26MB
  16. 10 - 2.4 Understand compatibility with Jupyter.mp4 258.05MB
  17. 11 - Learning objectives.mp4 28.81MB
  18. 12 - 3.1 Write procedural code.mp4 112.86MB
  19. 13 - 3.2 Use simple expressions and variables.mp4 173.93MB
  20. 14 - 3.3 Work with the built-in types.mp4 66.60MB
  21. 15 - 3.4 Learn to Print.mp4 70.60MB
  22. 16 - 3.5 Perform basic math operations.mp4 167.11MB
  23. 17 - 3.6 Use classes and objects with dot notation.mp4 194.46MB
  24. 18 - Learning objectives.mp4 17.00MB
  25. 19 - 4.1 Use string methods.mp4 131.93MB
  26. 20 - 4.2 Format strings.mp4 98.69MB
  27. 21 - 4.3 Manipulate strings - membership, slicing, and concatenation.mp4 136.75MB
  28. 22 - 4.4 Learn to use unicode.mp4 74.37MB
  29. 23 - Learning objectives.mp4 22.45MB
  30. 24 - 5.1 Use lists and tuples.mp4 369.96MB
  31. 25 - 5.2 Explore dictionaries.mp4 213.33MB
  32. 26 - 5.3 Dive into sets.mp4 83.03MB
  33. 27 - 5.4 Work with the numpy array.mp4 234.44MB
  34. 28 - 5.5 Use the Pandas DataFrame.mp4 116.78MB
  35. 29 - 5.6 Use the Pandas Series.mp4 71.62MB
  36. 30 - Learning objectives.mp4 24.00MB
  37. 31 - 6.1 Convert lists to dicts and back.mp4 74.45MB
  38. 32 - 6.2 Convert dicts to Pandas Dataframe.mp4 104.57MB
  39. 33 - 6.3 Convert characters to integers and back.mp4 35.73MB
  40. 34 - 6.4 Convert between hexadecimal, binary, and floats.mp4 101.36MB
  41. 35 - Learning objectives.mp4 24.93MB
  42. 36 - 7.1 Learn to loop with for loops.mp4 44.92MB
  43. 37 - 7.2 Repeat with while loops.mp4 50.23MB
  44. 38 - 7.3 Learn to handle exceptions.mp4 111.94MB
  45. 39 - 7.4 Use conditionals.mp4 168.25MB
  46. 40 - Learning objectives.mp4 22.46MB
  47. 41 - 8.1 Write and use functions.mp4 206.47MB
  48. 42 - 8.2 Learn to use decorators.mp4 210.94MB
  49. 43 - 8.3 Compose closure functions.mp4 132.86MB
  50. 44 - 8.4 Use lambdas.mp4 106.23MB
  51. 45 - 8.5 Advanced Use of Functions.mp4 319.02MB
  52. 46 - Learning objectives.mp4 33.79MB
  53. 47 - 9.1 Learn NumPy.mp4 287.95MB
  54. 48 - 9.2 Learn SciPy.mp4 664.99MB
  55. 49 - 9.3 Learn Pandas.mp4 335.61MB
  56. 50 - 9.4 Learn TensorFlow.mp4 341.90MB
  57. 51 - 9.5 Use Seaborn for 2D plots.mp4 261.65MB
  58. 52 - 9.6 Use Plotly for interactive plots.mp4 262.06MB
  59. 53 - 9.7 Specialized Visualization Libraries.mp4 241.69MB
  60. 54 - 9.8 Learn Natural Language Processing Libraries.mp4 124.95MB
  61. 55 - Learning objectives.mp4 27.70MB
  62. 56 - 10.1 Understand functional programming.mp4 151.13MB
  63. 57 - 10.2 Apply functions to data science workflows.mp4 47.12MB
  64. 58 - 10.3 Use map_reduce_filter.mp4 95.23MB
  65. 59 - 10.4 Use list comprehensions.mp4 98.27MB
  66. 60 - 10.5 Use dictionary comprehensions.mp4 15.45MB
  67. 61 - Learning objectives.mp4 17.83MB
  68. 62 - 11.1 Use generators.mp4 69.40MB
  69. 63 - 11.2 Design generator pipelines.mp4 141.25MB
  70. 64 - 11.3 Implement lazy evaluation functions.mp4 59.14MB
  71. 65 - Learning objectives.mp4 20.97MB
  72. 66 - 12.1 Perform simple pattern matching.mp4 97.05MB
  73. 67 - 12.2 Use regular expressions.mp4 284.59MB
  74. 68 - 12.3 Learn text processing techniques - Beautiful Soup.mp4 87.60MB
  75. 69 - Learning objectives.mp4 18.20MB
  76. 70 - 13.1 Sort in Python.mp4 186.66MB
  77. 71 - 13.2 Create custom sorting functions.mp4 229.33MB
  78. 72 - 13.3 Sort in Pandas.mp4 301.95MB
  79. 73 - Learning objectives.mp4 22.10MB
  80. 74 - 14.1 Read and write files - file, pickle, CSV, JSON.mp4 214.71MB
  81. 75 - 14.2 Read and write with Pandas - CSV, JSON.mp4 336.50MB
  82. 76 - 14.3 Read and write using web resources (requests, boto, github).mp4 110.86MB
  83. 77 - 14.4 Use function-based concurrency.mp4 608.14MB
  84. 78 - Learning objectives.mp4 20.91MB
  85. 79 - 15.1 Share with Github.mp4 358.09MB
  86. 80 - 15.2 Create Kaggle Kernels.mp4 207.48MB
  87. 81 - 15.3 Collaborate with Colab.mp4 125.18MB
  88. 82 - 15.4 Post public graphs with Plotly.mp4 103.50MB
  89. 83 - Learning Objectives.mp4 28.71MB
  90. 84 - 16.1 PyTest.mp4 372.92MB
  91. 85 - 16.2 Visual Studio Code.mp4 364.64MB
  92. 86 - 16.3 Vim.mp4 136.81MB
  93. 87 - 16.4 Ludwig (Open Source AutoML).mp4 146.48MB
  94. 88 - 16.5 Sklearn Algorithm Cheatsheet.mp4 104.05MB
  95. 89 - 16.6 Recommendations.mp4 47.75MB