[FreeCourseSite.com] Udemy - Complete Python for Data Science & Machine Learning from A-Z


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Creat Time:   2025-07-17
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Last Active:   2025-07-17
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Tags:    FreeCourseSite com Udemy - Complete Python for Data Science Machine Learning from A-Z
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File List

  1. 53. Competition Section on Kaggle/2. Competitions on Kaggle Lesson 2.mp4 191.75 MB
  2. 53. Competition Section on Kaggle/1. Competitions on Kaggle Lesson 1.mp4 188.16 MB
  3. 55. Code Section on Kaggle/3. Examining the Code Section in Kaggle Lesson 3.mp4 159.89 MB
  4. 54. Dataset Section on Kaggle/1. Datasets on Kaggle.mp4 133.17 MB
  5. 1. Installations/1. Installing Anaconda Distribution for Windows.mp4 130.37 MB
  6. 52. First Contact with Kaggle/1. What is Kaggle.mp4 129.73 MB
  7. 1. Installations/3. Installing Anaconda Distribution for Linux.mp4 127.26 MB
  8. 59. Introduction to Machine Learning with Real Hearth Attack Prediction Project/6. Recognizing Variables In Dataset.mp4 126.87 MB
  9. 52. First Contact with Kaggle/5. Getting to Know the Kaggle Homepage.mp4 122.93 MB
  10. 59. Introduction to Machine Learning with Real Hearth Attack Prediction Project/1. First Step to the Hearth Attack Prediction Project.mp4 117.22 MB
  11. 32. Matplotlib/8. Basic Plots in Matplotlib I.mp4 111.17 MB
  12. 57. Other Most Used Options on Kaggle/2. Ranking Among Users on Kaggle.mp4 107.07 MB
  13. 38. Linear Regression Algorithm in Machine Learning A-Z/3. Linear Regression Algorithm With Python Part 2.mp4 106.94 MB
  14. 55. Code Section on Kaggle/2. Examining the Code Section in Kaggle Lesson 2.mp4 105.81 MB
  15. 59. Introduction to Machine Learning with Real Hearth Attack Prediction Project/3. Notebook Design to be Used in the Project.mp4 104.98 MB
  16. 36. Evaluation Metrics in Machine Learning/2. Machine Learning Model Performance Evaluation Classification Error Metrics.mp4 100.29 MB
  17. 33. Seaborn/5. Basic Plots in Seaborn.mp4 98.83 MB
  18. 36. Evaluation Metrics in Machine Learning/4. Machine Learning With Python.mp4 92.27 MB
  19. 61. Preparation For Exploratory Data Analysis (EDA) in Data Science/4. Examining Statistics of Variables.mp4 91.35 MB
  20. 29. Functions That Can Be Applied on a DataFrame/3. Aggregation Functions in Pandas DataFrames.mp4 90.70 MB
  21. 63. Exploratory Data Analysis (EDA) - Bi-variate Analysis/14. Relationships between variables (Analysis with Heatmap) Lesson 2.mp4 90.66 MB
  22. 38. Linear Regression Algorithm in Machine Learning A-Z/5. Linear Regression Algorithm With Python Part 4.mp4 89.99 MB
  23. 29. Functions That Can Be Applied on a DataFrame/5. Coordinated Use of Grouping and Aggregation Functions in Pandas Dataframes.mp4 88.11 MB
  24. 62. Exploratory Data Analysis (EDA) - Uni-variate Analysis/4. Categoric Variables (Analysis with Pie Chart) Lesson 2.mp4 84.01 MB
  25. 58. Details on Kaggle/1. User Page Review on Kaggle.mp4 81.52 MB
  26. 40. Logistic Regression Algorithm in Machine Learning A-Z/3. Logistic Regression Algorithm with Python Part 2.mp4 81.46 MB
  27. 34. Geoplotlib/3. Example - 2.mp4 81.16 MB
  28. 62. Exploratory Data Analysis (EDA) - Uni-variate Analysis/1. Numeric Variables (Analysis with Distplot) Lesson 1.mp4 80.33 MB
  29. 55. Code Section on Kaggle/1. Examining the Code Section in Kaggle Lesson 1.mp4 79.56 MB
  30. 59. Introduction to Machine Learning with Real Hearth Attack Prediction Project/5. Examining the Project Topic.mp4 76.51 MB
  31. 38. Linear Regression Algorithm in Machine Learning A-Z/2. Linear Regression Algorithm With Python Part 1.mp4 76.18 MB
  32. 62. Exploratory Data Analysis (EDA) - Uni-variate Analysis/3. Categoric Variables (Analysis with Pie Chart) Lesson 1.mp4 74.76 MB
  33. 58. Details on Kaggle/2. Treasure in The Kaggle.mp4 74.67 MB
  34. 1. Installations/4. Reviewing The Jupyter Notebook.mp4 72.93 MB
  35. 40. Logistic Regression Algorithm in Machine Learning A-Z/2. Logistic Regression Algorithm with Python Part 1.mp4 72.24 MB
  36. 21. Operations in Numpy Library/2. Arithmetic Operations in Numpy.mp4 71.82 MB
  37. 38. Linear Regression Algorithm in Machine Learning A-Z/4. Linear Regression Algorithm With Python Part 3.mp4 70.30 MB
  38. 32. Matplotlib/4. Figure, Subplot and Axes.mp4 69.86 MB
  39. 63. Exploratory Data Analysis (EDA) - Bi-variate Analysis/10. Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 2.mp4 68.09 MB
  40. 26. Structural Operations on Pandas DataFrame/3. Null Values in Pandas Dataframes.mp4 67.00 MB
  41. 31. File Operations in Pandas Library/2. Data Entry with Csv and Txt Files.mp4 64.34 MB
  42. 60. First Organization/3. Initial analysis on the dataset.mp4 63.97 MB
  43. 28. Structural Concatenation Operations in Pandas DataFrame/1. Concatenating Pandas Dataframes Concat Function.mp4 63.89 MB
  44. 60. First Organization/1. Required Python Libraries.mp4 63.58 MB
  45. 32. Matplotlib/5. Figure Customization.mp4 63.29 MB
  46. 1. Installations/2. Installing Anaconda Distribution for MacOs.mp4 61.12 MB
  47. 28. Structural Concatenation Operations in Pandas DataFrame/4. Merge Pandas Dataframes Merge() Function Lesson 3.mp4 60.14 MB
  48. 33. Seaborn/7. Regression Plots and Squarify in Seaborn.mp4 60.10 MB
  49. 17. NumPy Library Introduction/3. The Power of NumPy.mp4 59.87 MB
  50. 42. K Nearest Neighbors Algorithm in Machine Learning A-Z/3. K Nearest Neighbors Algorithm with Python Part 2.mp4 59.37 MB

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