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[Udemy] Data Analysis In-Depth (In Python) ()

  • 收录时间:2022-03-20 09:20:09
  • 文件大小:21GB
  • 下载次数:1
  • 最近下载:2022-03-20 09:20:09
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文件列表

  1. 22. Day 20 A - EDA Cont.mp4 1GB
  2. 8. Day 8 - Statistics for Data Analysis - Statistical Hypothesis.mp4 1GB
  3. 18. Day 17 - Pandas.mp4 1GB
  4. 19. Day 18 - Seaborn.mp4 1GB
  5. 14. Day 13 - Numpy.mp4 1GB
  6. 12. Day 11 - Python for Data Analysis.mp4 1GB
  7. 6. Day 6 - Statistics for Data Analysis - Probability.mp4 1GB
  8. 5. Day 5 - Statistics for Data Analysis - Probability.mp4 1GB
  9. 17. Day 16 - Pandas.mp4 1GB
  10. 11. Day 10 - Python for Data Analysis.mp4 1GB
  11. 7. Day 7 - Statistics for Data Analysis - Probability.mp4 1GB
  12. 4. Day 4 - Statistics for Data Analysis - Probability.mp4 1012MB
  13. 1. Day 1 - Introduction to Data Science.mp4 888MB
  14. 13. Day 12 - Python for Data Analysis.mp4 855MB
  15. 15. Day 14 - Pandas.mp4 818MB
  16. 2. Day 2 - Introduction to Data Analytics.mp4 813MB
  17. 3. Day 3 - Statistics for Data Analysis - Scalar, Vectors and Matrix.mp4 810MB
  18. 16. Day 15 - Pandas.mp4 791MB
  19. 10. Day 9B - Python for Data Analysis.mp4 784MB
  20. 20. Day 19 A - Seaborn.mp4 587MB
  21. 21. Day 19 B - EDA.mp4 379MB
  22. 9. Day 9A - Statistics for Data Analysis - Statistical Hypothesis.mp4 251MB
  23. 23. Day 20 B - What Next.mp4 231MB
  24. 3.1 Machine _Learning Day 3.pdf 28MB
  25. 8.1 Machine _Learning Day 8.pdf 25MB
  26. 4.1 Machine _Learning Day 4.pdf 17MB
  27. 6.1 Machine _Learning Day 6.pdf 14MB
  28. 7.1 Machine _Learning Day 7.pdf 14MB
  29. 1.1 Machine _Learning Day 1.pdf 13MB
  30. 5.1 Machine _Learning Day 5.pdf 11MB
  31. 2.1 Machine _Learning Day 2.pdf 8MB
  32. 10.1 Machine _Learning - 9B.pdf 7MB
  33. 9.1 Machine _Learning 9A.pdf 6MB
  34. 14.1 Machine _Learning - 13.pdf 4MB
  35. 19.2 Machine _Learning - 18.pdf 4MB
  36. 15.2 Machine _Learning - 14.pdf 3MB
  37. 19.3 Seaborn.ipynb 2MB
  38. 12.1 images in pdf.pdf 2MB
  39. 21.2 LendingClub.ipynb 2MB
  40. 15.1 Machine _Learning - 14 - Practical.pdf 1MB
  41. 14.2 Practicals.zip 1MB
  42. 18.1 Machine _Learning - 17 - Practical.pdf 1MB
  43. 13.1 images in pdf.pdf 1013KB
  44. 16.1 Machine _Learning - 15 - Practical.pdf 998KB
  45. 6.2 Z Table 20210801.pdf 874KB
  46. 19.1 Machine _Learning - 18 - Practical.pdf 409KB
  47. 17.1 Machine _Learning - 16 - Practical.pdf 350KB
  48. 21.3 Machine _Learning - 19 B - Practical.pdf 247KB
  49. 22. Day 20 A - EDA Cont.srt 215KB
  50. 8. Day 8 - Statistics for Data Analysis - Statistical Hypothesis.srt 211KB
  51. 19. Day 18 - Seaborn.srt 203KB
  52. 3. Day 3 - Statistics for Data Analysis - Scalar, Vectors and Matrix.srt 198KB
  53. 6. Day 6 - Statistics for Data Analysis - Probability.srt 197KB
  54. 14. Day 13 - Numpy.srt 196KB
  55. 18. Day 17 - Pandas.srt 184KB
  56. 17. Day 16 - Pandas.srt 180KB
  57. 15. Day 14 - Pandas.srt 174KB
  58. 12. Day 11 - Python for Data Analysis.srt 174KB
  59. 11. Day 10 - Python for Data Analysis.srt 168KB
  60. 13. Day 12 - Python for Data Analysis.srt 166KB
  61. 4. Day 4 - Statistics for Data Analysis - Probability.srt 163KB
  62. 5. Day 5 - Statistics for Data Analysis - Probability.srt 162KB
  63. 1. Day 1 - Introduction to Data Science.srt 161KB
  64. 7. Day 7 - Statistics for Data Analysis - Probability.srt 160KB
  65. 10. Day 9B - Python for Data Analysis.srt 147KB
  66. 2. Day 2 - Introduction to Data Analytics.srt 147KB
  67. 16. Day 15 - Pandas.srt 120KB
  68. 20. Day 19 A - Seaborn.srt 100KB
  69. 15.3 Pandas practicals.zip 71KB
  70. 21. Day 19 B - EDA.srt 60KB
  71. 9. Day 9A - Statistics for Data Analysis - Statistical Hypothesis.srt 44KB
  72. 23. Day 20 B - What Next.srt 35KB
  73. 11.1 Python Notebook.zip 33KB
  74. 7.2 Reference Links.txt 284B
  75. 21.1 EDA Data .txt 84B