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[FreeCourseLab.com] Udemy - The Data Science Course 2019 Complete Data Science Bootcamp

FreeCourseLabUdemyDataScienceCourse2019CompleteBootcamp

种子大小：15.5 GB

收录时间：2026-03-04

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文件列表：1000File

  1. 16. Statistics - Practical Example Descriptive Statistics/1. Practical Example Descriptive Statistics.mp4160.47 MB
  2. 12. Probability Distributions/29. A Practical Example of Probability Distributions.mp4157.83 MB
  3. 11. Bayesian Inference/22. A Practical Example of Bayesian Inference.mp4156.61 MB
  4. 40. Part 6 Mathematics/16. Why is Linear Algebra Useful.mp4144.34 MB
  5. 5. The Field of Data Science - Popular Data Science Techniques/1. Techniques for Working with Traditional Data.mp4138.31 MB
  6. 10. Combinatorics/20. A Practical Example of Combinatorics.mp4134.15 MB
  7. 3. The Field of Data Science - Connecting the Data Science Disciplines/1. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.vtt126.88 MB
  8. 3. The Field of Data Science - Connecting the Data Science Disciplines/1. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.mp4126.88 MB
  9. 5. The Field of Data Science - Popular Data Science Techniques/15. Types of Machine Learning.mp4125.15 MB
  10. 5. The Field of Data Science - Popular Data Science Techniques/10. Techniques for Working with Traditional Methods.mp4123.52 MB
  11. 56. Software Integration/5. Taking a Closer Look at APIs.mp4115.6 MB
  12. 20. Statistics - Hypothesis Testing/4. Rejection Region and Significance Level.mp4112.61 MB
  13. 2. The Field of Data Science - The Various Data Science Disciplines/7. Continuing with BI, ML, and AI.mp4108.98 MB
  14. 56. Software Integration/3. What are Data Connectivity, APIs, and Endpoints.mp4104.09 MB
  15. 6. The Field of Data Science - Popular Data Science Tools/1. Necessary Programming Languages and Software Used in Data Science.mp4103.52 MB
  16. 55. Appendix Deep Learning - TensorFlow 1 Business Case/4. Business Case Preprocessing.mp4103.41 MB
  17. 19. Statistics - Practical Example Inferential Statistics/1. Practical Example Inferential Statistics.mp4102.67 MB
  18. 5. The Field of Data Science - Popular Data Science Techniques/13. Machine Learning (ML) Techniques.mp499.32 MB
  19. 13. Probability in Other Fields/1. Probability in Finance.mp499.07 MB
  20. 35. Advanced Statistical Methods - Practical Example Linear Regression/1. Practical Example Linear Regression (Part 1).mp497.09 MB
  21. 51. Deep Learning - Business Case Example/4. Business Case Preprocessing the Data.mp492.05 MB
  22. 20. Statistics - Hypothesis Testing/1. Null vs Alternative Hypothesis.mp492.04 MB
  23. 12. Probability Distributions/3. Types of Probability Distributions.mp491.59 MB
  24. 5. The Field of Data Science - Popular Data Science Techniques/7. Business Intelligence (BI) Techniques.mp489.95 MB
  25. 55. Appendix Deep Learning - TensorFlow 1 Business Case/1. Business Case Getting acquainted with the dataset.mp487.66 MB
  26. 36. Advanced Statistical Methods - Logistic Regression/3. Logistic vs Logit Function.mp486.5 MB
  27. 9. Part 2 Probability/1. The Basic Probability Formula.mp485.92 MB
  28. 12. Probability Distributions/15. Characteristics of Continuous Distributions.mp484.12 MB
  29. 2. The Field of Data Science - The Various Data Science Disciplines/1. Data Science and Business Buzzwords Why are there so many.mp481.41 MB
  30. 4. The Field of Data Science - The Benefits of Each Discipline/1. The Reason behind these Disciplines.mp481.19 MB
  31. 58. Case Study - Preprocessing the 'Absenteeism_data'/11. Obtaining Dummies from a Single Feature.mp481.11 MB
  32. 18. Statistics - Inferential Statistics Confidence Intervals/3. Confidence Intervals; Population Variance Known; z-score.mp478.21 MB
  33. 51. Deep Learning - Business Case Example/1. Business Case Exploring the Dataset and Identifying Predictors.mp478.09 MB
  34. 13. Probability in Other Fields/2. Probability in Statistics.mp477.29 MB
  35. 55. Appendix Deep Learning - TensorFlow 1 Business Case/6. Creating a Data Provider.mp476.35 MB
  36. 9. Part 2 Probability/3. Computing Expected Values.mp475.69 MB
  37. 5. The Field of Data Science - Popular Data Science Techniques/4. Techniques for Working with Big Data.mp475.51 MB
  38. 22. Part 4 Introduction to Python/3. Why Python.mp475.08 MB
  39. 58. Case Study - Preprocessing the 'Absenteeism_data'/16. Classifying the Various Reasons for Absence.mp474.61 MB
  40. 38. Advanced Statistical Methods - K-Means Clustering/13. How is Clustering Useful.mp474.46 MB
  41. 12. Probability Distributions/1. Fundamentals of Probability Distributions.mp473.41 MB
  42. 8. The Field of Data Science - Debunking Common Misconceptions/1. Debunking Common Misconceptions.mp472.86 MB
  43. 56. Software Integration/9. Software Integration - Explained.mp472.65 MB
  44. 15. Statistics - Descriptive Statistics/1. Types of Data.mp472.52 MB
  45. 37. Advanced Statistical Methods - Cluster Analysis/2. Some Examples of Clusters.mp471.53 MB
  46. 18. Statistics - Inferential Statistics Confidence Intervals/12. Confidence intervals. Two means. Dependent samples.mp470.47 MB
  47. 21. Statistics - Practical Example Hypothesis Testing/1. Practical Example Hypothesis Testing.mp469.49 MB
  48. 56. Software Integration/1. What are Data, Servers, Clients, Requests, and Responses.mp469.04 MB
  49. 12. Probability Distributions/11. Discrete Distributions The Binomial Distribution.mp468.83 MB
  50. 2. The Field of Data Science - The Various Data Science Disciplines/9. A Breakdown of our Data Science Infographic.mp467.75 MB
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