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[Udemy] Statistics & Mathematics for Data Science in Python [2020, ENG]

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视频 2022-1-2 12:35 2024-12-23 18:11 215 720.75 MB 72
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Udemy Statistics & Mathematics for Data Science in Python 2020 ENG

文件列表
  1. 5. Confidence Intervals & Hypothesis Testing/10. Summary.mp4503.67KB
  2. 1. Google Colab for Data Science/8. Summary.mp4563.49KB
  3. 8. Natural Language Processing/9. Summary.mp4649.49KB
  4. 3. Distribution Types/1. Introduction.mp4685.56KB
  5. 2. Vocabulary & Descriptive Statistics/1. Introduction.mp4688.01KB
  6. 6. Regression & Predictions/1. Introduction.mp4721.31KB
  7. 7. Classification Modeling/11. Summary.mp4760.11KB
  8. 8. Natural Language Processing/1. Introduction.mp4770.6KB
  9. 4. Inferential Statistics with Visualizations/7. Summary.mp4831.27KB
  10. 5. Confidence Intervals & Hypothesis Testing/1. Introduction.mp4852.66KB
  11. 7. Classification Modeling/1. Introduction.mp4899.62KB
  12. 2. Vocabulary & Descriptive Statistics/7. Summary.mp4923.97KB
  13. 1. Google Colab for Data Science/2. Introduction.mp4974.6KB
  14. 4. Inferential Statistics with Visualizations/1. Introduction.mp41.02MB
  15. 6. Regression & Predictions/12. Summary.mp41.09MB
  16. 1. Google Colab for Data Science/3. Google Drive & Colab Introduction.mp42.18MB
  17. 3. Distribution Types/8. Summary.mp42.5MB
  18. 1. Google Colab for Data Science/1. Course Overview.mp42.63MB
  19. 1. Google Colab for Data Science/7. Sharing a Colab Notebook.mp42.9MB
  20. 3. Distribution Types/2. Introduction to Probability Distributions.mp43.11MB
  21. 1. Google Colab for Data Science/4. Documentation Exploration.mp44.59MB
  22. 7. Classification Modeling/8. Random Forest.mp45.02MB
  23. 8. Natural Language Processing/6. Finding Features of Textual Data.mp45.23MB
  24. 5. Confidence Intervals & Hypothesis Testing/3. Introduction to Confidence Intervals & Tests.mp46.11MB
  25. 7. Classification Modeling/6. K-Nearest Neighbors.mp46.41MB
  26. 8. Natural Language Processing/7. Naive Bayes with NLTK.mp46.64MB
  27. 8. Natural Language Processing/4. For Loop Creation of 8.2.mp46.95MB
  28. 8. Natural Language Processing/3. NLTK to Examine Text.mp47.6MB
  29. 7. Classification Modeling/5. Logistic Regression.mp47.99MB
  30. 8. Natural Language Processing/5. Movie Reviews Text Analysis & Frequency.mp48.22MB
  31. 3. Distribution Types/5. Poisson Distribution.mp48.58MB
  32. 2. Vocabulary & Descriptive Statistics/2. Introduction to General Statistical Vocabulary.mp49.4MB
  33. 6. Regression & Predictions/6. Ridge Regression.mp49.67MB
  34. 6. Regression & Predictions/9. Random Forest Regression.mp49.8MB
  35. 7. Classification Modeling/10. Model Hyper Tuning & Optimization.mp410.16MB
  36. 7. Classification Modeling/7. SVM.mp410.27MB
  37. 7. Classification Modeling/2. Preparation Part 1 Loading & Exploring Penguins Data.mp410.4MB
  38. 8. Natural Language Processing/2. Data Loading & Exploration.mp410.49MB
  39. 3. Distribution Types/3. Uniform Distribution.mp411.02MB
  40. 6. Regression & Predictions/5. Polynomial Regression.mp411.17MB
  41. 2. Vocabulary & Descriptive Statistics/6. Correlation Coefficient.mp411.39MB
  42. 4. Inferential Statistics with Visualizations/5. Scatter Plots.mp411.44MB
  43. 5. Confidence Intervals & Hypothesis Testing/2. Seaborn Sample Data & Fitting.mp411.5MB
  44. 3. Distribution Types/4. Binomial Distribution.mp411.57MB
  45. 7. Classification Modeling/4. Naive Bayes.mp411.73MB
  46. 6. Regression & Predictions/8. ElasticNet Regression.mp412.14MB
  47. 1. Google Colab for Data Science/5. Importing Data from Google Drive to Pandas DataFrame.mp412.33MB
  48. 4. Inferential Statistics with Visualizations/4. Box Plots.mp412.72MB
  49. 6. Regression & Predictions/7. Lasso Regression.mp412.76MB
  50. 4. Inferential Statistics with Visualizations/3. Histograms.mp412.77MB
  51. 1. Google Colab for Data Science/6. Importing Data from OneDrive to Pandas DataFrame.mp412.85MB
  52. 5. Confidence Intervals & Hypothesis Testing/4. Assuming Normality.mp413.35MB
  53. 4. Inferential Statistics with Visualizations/2. Bar Charts.mp414.36MB
  54. 5. Confidence Intervals & Hypothesis Testing/8. ANOVA.mp414.39MB
  55. 3. Distribution Types/6. Normal Distribution.mp415.11MB
  56. 7. Classification Modeling/3. Preparation Part 2 Cleaning & Preparing Penguins Data.mp415.94MB
  57. 4. Inferential Statistics with Visualizations/6. Advanced Visualizations.mp415.95MB
  58. 2. Vocabulary & Descriptive Statistics/5. Measures of Center, Essential Analytics.mp416.14MB
  59. 5. Confidence Intervals & Hypothesis Testing/5. Normal DataProbability Plots with Means.mp416.65MB
  60. 2. Vocabulary & Descriptive Statistics/4. Summarizing Data with Counts.mp416.91MB
  61. 3. Distribution Types/7. Fitting Distributions - Advanced.mp417.05MB
  62. 6. Regression & Predictions/11. Model Hyper Tuning & Optimization.mp417.43MB
  63. 6. Regression & Predictions/2. Preparation Part 1 Loading & Exploring Diamonds Data.mp418.39MB
  64. 2. Vocabulary & Descriptive Statistics/3. Variable Types within Data.mp419.13MB
  65. 8. Natural Language Processing/8. Cosine Similarity Between Texts.mp419.84MB
  66. 6. Regression & Predictions/4. Linear Regression.mp420.72MB
  67. 7. Classification Modeling/9. Model Comparison Tool.mp420.88MB
  68. 6. Regression & Predictions/10. Model Comparison Tool.mp421.89MB
  69. 5. Confidence Intervals & Hypothesis Testing/9. Non-Normal Data & Bootstrap.mp423.4MB
  70. 5. Confidence Intervals & Hypothesis Testing/6. Normal Data Categorical Confidence Intervals.mp425.48MB
  71. 6. Regression & Predictions/3. Preparation Part 2 Categorical Coding & Data Splitting.mp425.79MB
  72. 5. Confidence Intervals & Hypothesis Testing/7. Normal Data Quantitative Confidence Intervals.mp428MB
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