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LinkedIn Learning - Data Science Foundations Fundamentals

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文件列表

  1. [3] 2. The Place of Data Science in the Data Universe/[3] Deep learning neural networks.mp4 31MB
  2. [3] 2. The Place of Data Science in the Data Universe/[2] Machine learning.mp4 30MB
  3. [5] 4. Sources of Data/[5] Scraping data.mp4 30MB
  4. [3] 2. The Place of Data Science in the Data Universe/[1] Artificial intelligence.mp4 30MB
  5. [9] 8. Analyses for Data Science/[2] Predictive models.mp4 25MB
  6. [6] 5. Sources of Rules/[2] The derivation of rules from data analysis.mp4 24MB
  7. [2] 1. What Is Data Science/[3] The data science pathway.mp4 23MB
  8. [9] 8. Analyses for Data Science/[1] Descriptive analyses.mp4 23MB
  9. [5] 4. Sources of Data/[3] Open data.mp4 21MB
  10. [9] 8. Analyses for Data Science/[7] Dimensionality reduction.mp4 19MB
  11. [9] 8. Analyses for Data Science/[3] Trend analysis.mp4 19MB
  12. [9] 8. Analyses for Data Science/[4] Clustering.mp4 18MB
  13. [9] 8. Analyses for Data Science/[9] Validating models.mp4 18MB
  14. [9] 8. Analyses for Data Science/[6] Anomaly detection.mp4 18MB
  15. [9] 8. Analyses for Data Science/[8] Feature selection and creation.mp4 17MB
  16. [7] 6. Tools for Data Science/[1] Applications for data analysis.mp4 15MB
  17. [9] 8. Analyses for Data Science/[10] Aggregating models.mp4 15MB
  18. [5] 4. Sources of Data/[1] Data preparation.mp4 15MB
  19. [3] 2. The Place of Data Science in the Data Universe/[4] Big data.mp4 15MB
  20. [8] 7. Mathematics for Data Science/[1] Algebra.mp4 15MB
  21. [5] 4. Sources of Data/[6] Creating data.mp4 15MB
  22. [2] 1. What Is Data Science/[4] Roles and teams in data science.mp4 14MB
  23. [3] 2. The Place of Data Science in the Data Universe/[6] Prescriptive analytics.mp4 14MB
  24. [5] 4. Sources of Data/[8] Self-generated data.mp4 14MB
  25. [8] 7. Mathematics for Data Science/[3] Optimization and the combinatorial explosion.mp4 14MB
  26. [5] 4. Sources of Data/[7] Passive collection of training data.mp4 13MB
  27. [9] 8. Analyses for Data Science/[5] Classifying.mp4 13MB
  28. [7] 6. Tools for Data Science/[2] Languages for data science.mp4 13MB
  29. [6] 5. Sources of Rules/[1] The enumeration of explicit rules.mp4 13MB
  30. [4] 3. Ethics and Agency/[2] Agency of algorithms and decision-makers.mp4 13MB
  31. [4] 3. Ethics and Agency/[1] Legal, ethical, and social issues of data science.mp4 13MB
  32. [3] 2. The Place of Data Science in the Data Universe/[5] Predictive analytics.mp4 12MB
  33. [1] Introduction/[1] The fundamentals of data science.mp4 12MB
  34. [7] 6. Tools for Data Science/[3] Machine learning as a service.mp4 11MB
  35. [3] 2. The Place of Data Science in the Data Universe/[7] Business intelligence.mp4 11MB
  36. [8] 7. Mathematics for Data Science/[4] Bayes' theorem.mp4 11MB
  37. [5] 4. Sources of Data/[4] APIs.mp4 11MB
  38. [11] Conclusion/[1] Next steps.mp4 10MB
  39. [10] 9. Acting on Data Science/[1] Interpretability.mp4 9MB
  40. [6] 5. Sources of Rules/[3] The generation of implicit rules.mp4 9MB
  41. [8] 7. Mathematics for Data Science/[2] Calculus.mp4 9MB
  42. [2] 1. What Is Data Science/[2] The data science Venn diagram.mp4 9MB
  43. [2] 1. What Is Data Science/[1] Supply and demand for data science.mp4 8MB
  44. [10] 9. Acting on Data Science/[2] Actionable insights.mp4 8MB
  45. [5] 4. Sources of Data/[2] In-house data.mp4 6MB
  46. logo.jpg 72KB
  47. [3] 2. The Place of Data Science in the Data Universe/[1] Artificial intelligence.srt 14KB
  48. [9] 8. Analyses for Data Science/[2] Predictive models.srt 14KB
  49. [3] 2. The Place of Data Science in the Data Universe/[2] Machine learning.srt 14KB
  50. [3] 2. The Place of Data Science in the Data Universe/[6] Prescriptive analytics.srt 14KB
  51. [8] 7. Mathematics for Data Science/[1] Algebra.srt 13KB
  52. [9] 8. Analyses for Data Science/[1] Descriptive analyses.srt 12KB
  53. [3] 2. The Place of Data Science in the Data Universe/[3] Deep learning neural networks.srt 12KB
  54. [9] 8. Analyses for Data Science/[3] Trend analysis.srt 12KB
  55. [8] 7. Mathematics for Data Science/[3] Optimization and the combinatorial explosion.srt 12KB
  56. [9] 8. Analyses for Data Science/[8] Feature selection and creation.srt 11KB
  57. [9] 8. Analyses for Data Science/[4] Clustering.srt 10KB
  58. [5] 4. Sources of Data/[6] Creating data.srt 10KB
  59. [9] 8. Analyses for Data Science/[5] Classifying.srt 10KB
  60. [9] 8. Analyses for Data Science/[7] Dimensionality reduction.srt 10KB
  61. [2] 1. What Is Data Science/[3] The data science pathway.srt 10KB
  62. [3] 2. The Place of Data Science in the Data Universe/[4] Big data.srt 10KB
  63. [5] 4. Sources of Data/[1] Data preparation.srt 9KB
  64. [9] 8. Analyses for Data Science/[6] Anomaly detection.srt 9KB
  65. [4] 3. Ethics and Agency/[2] Agency of algorithms and decision-makers.srt 9KB
  66. [5] 4. Sources of Data/[3] Open data.srt 9KB
  67. [5] 4. Sources of Data/[5] Scraping data.srt 9KB
  68. [3] 2. The Place of Data Science in the Data Universe/[5] Predictive analytics.srt 9KB
  69. [9] 8. Analyses for Data Science/[9] Validating models.srt 8KB
  70. [2] 1. What Is Data Science/[4] Roles and teams in data science.srt 8KB
  71. [7] 6. Tools for Data Science/[1] Applications for data analysis.srt 8KB
  72. [2] 1. What Is Data Science/[2] The data science Venn diagram.srt 8KB
  73. [8] 7. Mathematics for Data Science/[2] Calculus.srt 8KB
  74. [8] 7. Mathematics for Data Science/[4] Bayes' theorem.srt 8KB
  75. [4] 3. Ethics and Agency/[1] Legal, ethical, and social issues of data science.srt 8KB
  76. [6] 5. Sources of Rules/[2] The derivation of rules from data analysis.srt 8KB
  77. [6] 5. Sources of Rules/[1] The enumeration of explicit rules.srt 7KB
  78. [3] 2. The Place of Data Science in the Data Universe/[7] Business intelligence.srt 7KB
  79. [5] 4. Sources of Data/[7] Passive collection of training data.srt 7KB
  80. [9] 8. Analyses for Data Science/[10] Aggregating models.srt 7KB
  81. [2] 1. What Is Data Science/[1] Supply and demand for data science.srt 7KB
  82. [7] 6. Tools for Data Science/[2] Languages for data science.srt 7KB
  83. [6] 5. Sources of Rules/[3] The generation of implicit rules.srt 6KB
  84. [5] 4. Sources of Data/[8] Self-generated data.srt 6KB
  85. [10] 9. Acting on Data Science/[1] Interpretability.srt 6KB
  86. [7] 6. Tools for Data Science/[3] Machine learning as a service.srt 6KB
  87. [11] Conclusion/[1] Next steps.srt 5KB
  88. [10] 9. Acting on Data Science/[2] Actionable insights.srt 5KB
  89. [5] 4. Sources of Data/[4] APIs.srt 5KB
  90. [5] 4. Sources of Data/[2] In-house data.srt 4KB
  91. [1] Introduction/[1] The fundamentals of data science.srt 2KB
  92. !!! More Courses !!!.txt 1KB