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[] Udemy - Data Science with Python - Beginners

  • 收录时间:2019-11-25 15:38:03
  • 文件大小:1GB
  • 下载次数:95
  • 最近下载:2021-01-20 14:15:14
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文件列表

  1. 6. Gradient Descent/4. Creating Normal Histogram.mp4 65MB
  2. 4. Linear Algebra/4. Understanding Central Tendencies.mp4 63MB
  3. 5. Probability/7. Defining the Next Value.mp4 60MB
  4. 6. Gradient Descent/1. Value Import.mp4 59MB
  5. 6. Gradient Descent/3. Working with Data Analysis.mp4 56MB
  6. 4. Linear Algebra/2. Matrices in Linear Algebra.mp4 53MB
  7. 6. Gradient Descent/2. Output Functions for Gradient.mp4 52MB
  8. 5. Probability/6. Example on Hypothesis Testing.mp4 49MB
  9. 6. Gradient Descent/5. Two Dimensional Graph.mp4 49MB
  10. 6. Gradient Descent/6. Multiple Scatter Plots.mp4 46MB
  11. 5. Probability/2. Normal Distribution Curve.mp4 44MB
  12. 6. Gradient Descent/8. Learnig Box Plots.mp4 40MB
  13. 3. Advanced Python/4. Creating Bar Charts.mp4 39MB
  14. 5. Probability/2. Normal Distribution Curve.vtt 38MB
  15. 5. Probability/4. Central Limit Theorem.mp4 37MB
  16. 4. Linear Algebra/1. Vector Spaces in Linear Algebra.mp4 35MB
  17. 3. Advanced Python/6. Understanding Scattered Plots.mp4 35MB
  18. 6. Gradient Descent/7. Analyzing Data Sets.mp4 35MB
  19. 4. Linear Algebra/5. Dispersion for Data.mp4 34MB
  20. 5. Probability/3. Example for Normal Distribution Curve.mp4 33MB
  21. 5. Probability/12. Example on Gradient Descent.mp4 32MB
  22. 5. Probability/10. Line of Best Fit.mp4 31MB
  23. 3. Advanced Python/5. Analysis on Line Chart.mp4 30MB
  24. 4. Linear Algebra/3. Analysing Statistical Data.mp4 29MB
  25. 2. What is Data Science/3. Various Python Scripts.mp4 29MB
  26. 5. Probability/9. Understanding Bayesian Inference.mp4 28MB
  27. 2. What is Data Science/2. Python Environment Framework.mp4 28MB
  28. 5. Probability/8. Principle of P Hacking.mp4 27MB
  29. 3. Advanced Python/1. Concept of Advanced Python.mp4 27MB
  30. 5. Probability/5. Concept of Hypothesis.mp4 26MB
  31. 3. Advanced Python/2. Creating Functions for Python.mp4 24MB
  32. 3. Advanced Python/3. Creating a New Library.mp4 23MB
  33. 5. Probability/1. Probability in Discreet Mathematics.mp4 21MB
  34. 2. What is Data Science/1. Understanding Data Science.mp4 18MB
  35. 1. Introduction/1. Introduction to Data Visualization.mp4 17MB
  36. 5. Probability/11. Datascience with Gradient Descent.mp4 14MB
  37. 7. Conclusion/1. Overview and Conclusion.mp4 13MB
  38. 1. Introduction/1.1 Data Science with Python.zip.zip 889KB
  39. 4. Linear Algebra/2. Matrices in Linear Algebra.vtt 10KB
  40. 4. Linear Algebra/4. Understanding Central Tendencies.vtt 10KB
  41. 6. Gradient Descent/3. Working with Data Analysis.vtt 8KB
  42. 3. Advanced Python/4. Creating Bar Charts.vtt 8KB
  43. 5. Probability/7. Defining the Next Value.vtt 8KB
  44. 5. Probability/6. Example on Hypothesis Testing.vtt 6KB
  45. 2. What is Data Science/3. Various Python Scripts.vtt 6KB
  46. 6. Gradient Descent/4. Creating Normal Histogram.vtt 6KB
  47. 4. Linear Algebra/1. Vector Spaces in Linear Algebra.vtt 6KB
  48. 3. Advanced Python/1. Concept of Advanced Python.vtt 6KB
  49. 5. Probability/4. Central Limit Theorem.vtt 6KB
  50. 6. Gradient Descent/1. Value Import.vtt 6KB
  51. 4. Linear Algebra/3. Analysing Statistical Data.vtt 6KB
  52. 6. Gradient Descent/6. Multiple Scatter Plots.vtt 6KB
  53. 2. What is Data Science/1. Understanding Data Science.vtt 6KB
  54. 3. Advanced Python/6. Understanding Scattered Plots.vtt 6KB
  55. 6. Gradient Descent/8. Learnig Box Plots.vtt 6KB
  56. 6. Gradient Descent/5. Two Dimensional Graph.vtt 6KB
  57. 3. Advanced Python/5. Analysis on Line Chart.vtt 6KB
  58. 6. Gradient Descent/2. Output Functions for Gradient.vtt 6KB
  59. 6. Gradient Descent/7. Analyzing Data Sets.vtt 5KB
  60. 4. Linear Algebra/5. Dispersion for Data.vtt 5KB
  61. 5. Probability/3. Example for Normal Distribution Curve.vtt 5KB
  62. 5. Probability/9. Understanding Bayesian Inference.vtt 5KB
  63. 2. What is Data Science/2. Python Environment Framework.vtt 5KB
  64. 5. Probability/12. Example on Gradient Descent.vtt 5KB
  65. 1. Introduction/1. Introduction to Data Visualization.vtt 5KB
  66. 3. Advanced Python/3. Creating a New Library.vtt 5KB
  67. 3. Advanced Python/2. Creating Functions for Python.vtt 4KB
  68. 5. Probability/8. Principle of P Hacking.vtt 4KB
  69. 5. Probability/10. Line of Best Fit.vtt 4KB
  70. 5. Probability/1. Probability in Discreet Mathematics.vtt 4KB
  71. 5. Probability/5. Concept of Hypothesis.vtt 4KB
  72. 7. Conclusion/1. Overview and Conclusion.vtt 4KB
  73. 5. Probability/11. Datascience with Gradient Descent.vtt 4KB
  74. [FCS Forum].url 133B
  75. [FreeCourseSite.com].url 127B
  76. [CourseClub.NET].url 123B