Logistic Regression in Python

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Logistic Regression in Python
Language
English
Category
Other
Size
102 bytes
Added
2026-07-23 03:06 (3 months, 2 weeks ago)
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3 seeders, 4 leechers (checked 6 days, 14 hours ago)
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Files
  1. Bonus Resources.txt102 bytes
  2. Get Bonus Downloads Here.url204 bytes
  3. 1 - 00-Introduction-01-py.pdf472.2 KB
  4. 1 - Welcome To The Course.mp425.3 MB
  5. 2 - Course Resources.html102 bytes
  6. Customer.csv64.0 KB
  7. House-Price.csv50.6 KB
  8. Classification.ipynb171.7 KB
  9. 02_whynot_linear.pdf155.3 KB
  10. 03_logistic.pdf352.7 KB
  11. 04_.pdf165.3 KB
  12. 04_P_value.pdf228.0 KB
  13. 05_Multiple_predictors.pdf151.3 KB
  14. 06_Confusion matrix.pdf222.3 KB
  15. 07_LDA.pdf183.1 KB
  16. 08_ROC.pdf306.9 KB
  17. 09_KNN.pdf236.7 KB
  18. 76 - The Problem Statement.mp414.2 MB
  19. 77 - Basic Equations And Ordinary Least Squares Ols Method.mp465.1 MB
  20. 78 - Assessing Accuracy Of Predicted Coefficients.mp4139.8 MB
  21. 79 - Assessing Model Accuracy Rse And R Squared.mp466.6 MB
  22. 80 - Simple Linear Regression In Python.mp489.7 MB
  23. 81 - Multiple Linear Regression.mp452.4 MB
  24. 82 - The F Statistic.mp486.7 MB
  25. 83 - Interpreting Results Of Categorical Variables.mp433.6 MB
  26. 84 - Multiple Linear Regression In Python.mp4100.8 MB
  27. 85 - Loan-Log.ipynb127.3 KB
  28. 85 - Practical Task 1.html1.0 KB
  29. 86 - Practical Task 2.html1.1 KB
  30. 87 - Practical Task 3.html3.3 KB
  31. 88 - Comprehensive Interview Preparation Questions.html1.4 KB
  32. Loan.ipynb213.0 KB
  33. Loan.xlsx25.6 KB
  34. Loan.xlsx - loan_data.csv19.8 KB
  35. 10 - Exercise-1.pdf553.8 KB
  36. 10 - Practice Exercise 1.html307 bytes
  37. 11 - Measures Of Dispersion.mp414.4 MB
  38. 12 - Exercise-2.pdf469.9 KB
  39. 12 - Practice Exercise 2.html307 bytes
  40. 13 - Installing Python And Anaconda.mp415.3 MB
  41. 14 - Opening Jupyter Notebook.mp454.7 MB
  42. 15 - Introduction To Jupyter.mp436.4 MB
  43. 16 - Arithmetic Operators In Python Python Basics.mp410.5 MB
  44. 17 - Strings In Python Python Basics.mp481.4 MB
  45. 18 - Lists Part 1.mp411.3 MB
  46. 19 - Lists Part 2.mp413.4 MB
  47. 20 - Tuples And Dictionaries.mp413.0 MB
  48. 21 - Working With Numpy Library Of Python.mp452.9 MB
  49. 22 - Customer.csv64.0 KB
  50. 22 - Working With Pandas Library Of Python.mp455.9 MB
  51. 23 - Working With Seaborn Library Of Python.mp461.7 MB
  52. 24 - Python File For Additional Practice.html307 bytes
  53. 24 - Reference-Guide-for-Python-practice.ipynb80.2 KB
  54. 25 - About The Upcoming Role Play.html1.1 KB
  55. 26 - Gathering Business Knowledge.mp48.7 MB
  56. 27 - Data Exploration.mp414.6 MB
  57. 28 - House-Price.csv50.6 KB
  58. 28 - The Dataset And The Data Dictionary.mp4127.4 MB
  59. 29 - Data Import In Python.mp435.5 MB
  60. 29 - House-Price.csv50.6 KB
  61. 30 - Movie-collection.csv55.8 KB
  62. 30 - Project Exercise 1.html512 bytes
  63. 31 - 03-04-PDE-Univariate-Analysis-Uni.pdf333.4 KB
  64. 31 - Univariate Analysis And Edd.mp419.0 MB
  65. 32 - Edd In Python.mp4123.8 MB
  66. 33 - Project Exercise 2.html204 bytes
  67. 34 - 04-06-PDE-Outlier-Treatment.pdf355.1 KB
  68. 34 - Outlier Treatment.mp416.2 MB
  69. 35 - Outlier Treatment In Python.mp476.5 MB
  70. 36 - Project Exercise 3.html204 bytes
  71. 37 - 04-05-PDE-Missing-value.pdf315.7 KB
  72. 37 - Missing Value Imputation.mp415.4 MB
  73. 38 - Missing Value Imputation In Python.mp434.5 MB
  74. 39 - Project Exercise 4.html204 bytes
  75. 40 - 04-07-PDE-Seasonality.pdf364.1 KB
  76. 40 - Seasonality In Data.mp412.3 MB
  77. 41 - 04-07-Variable-Transformation.pdf456.1 KB
  78. 41 - Variable Transformation.mp422.1 MB
  79. 42 - Variable Transformation And Deletion In Python.mp439.9 MB
  80. 43 - Project Exercise 5.html204 bytes
  81. 44 - 04-11-Dummy-Var.pdf163.0 KB
  82. 44 - Dummy Variable Creation Handling Qualitative Data.mp421.7 MB
  83. 45 - Dummy Variable Creation In Python.mp443.7 MB
  84. 46 - Project Exercise 6.html204 bytes
  85. 47 - 01-INtro.pdf190.4 KB
  86. 47 - Three Classifiers And The Problem Statement.mp431.8 MB
  87. 48 - 02-whynot-linear.pdf155.3 KB
  88. 48 - Why Cant We Use Linear Regression.mp428.0 MB
  89. 49 - 03-logistic.pdf352.7 KB
  90. 49 - Logistic Regression.mp455.0 MB
  91. 50 - Training A Simple Logistic Model In Python.mp476.1 MB
  92. 51 - Project Exercise 7.html307 bytes
  93. 52 - 04-P-value.pdf228.0 KB
  94. 52 - Result Of Simple Logistic Regression.mp444.3 MB
  95. 53 - 05-Multiple-predictors.pdf151.3 KB
  96. 53 - Logistic With Multiple Predictors.mp413.6 MB
  97. 54 - Training Multiple Predictor Logistic Model In Python.mp440.9 MB
  98. 55 - Project Exercise 8.html307 bytes
  99. 56 - 06-Confusion-matrix.pdf222.3 KB
  100. 56 - Confusion Matrix.mp440.1 MB
  101. 57 - Creating Confusion Matrix In Python.mp475.4 MB
  102. 58 - 08-ROC.pdf306.9 KB
  103. 58 - Evaluating Performance Of Model.mp460.1 MB
  104. 59 - Evaluating Model Performance In Python.mp414.4 MB
  105. 60 - Project Exercise 9.html204 bytes
  106. 61 - 07-LDA.pdf183.1 KB
  107. 61 - Linear Discriminant Analysis.mp467.7 MB
  108. 62 - Lda In Python.mp417.0 MB
  109. 63 - Project Exercise 10.html204 bytes
  110. 64 - 10-Test-Train.pdf238.7 KB
  111. 64 - Testtrain Split.mp464.6 MB
  112. 65 - More About Testtrain Split.html512 bytes
  113. 66 - Testtrain Split In Python.mp452.4 MB
  114. 67 - Project Exercise 11.html204 bytes
  115. 6 - 01-01-Lecture-TypesOfData.pdf177.7 KB
  116. 6 - Types Of Data.mp420.7 MB
  117. 7 - 01-02-Lecture-TypesOfStatistics.pdf171.7 KB
  118. 7 - Types Of Statistics.mp47.9 MB
  119. 8 - 01-03-Lecture-DataSummaryandGraph.pdf317.9 KB
  120. 8 - Describing Data Graphically.mp461.5 MB
  121. 9 - 01-04-Lecture-Centers.pdf313.0 KB
  122. 9 - Measures Of Centers.mp429.8 MB
  123. 3 - Introduction To Machine Learning.mp4145.6 MB
  124. 3 - Lecture-machineLearning.pdf991.6 KB
  125. 4 - This Is A Milestone.mp470.7 MB
  126. 5 - Building A Machine Learning Model.mp427.7 MB
  127. 89 - The Final Milestone.mp48.4 MB
  128. 90 - About Your Certificate.html921 bytes
  129. 91 - Bonus Lecture.html9.1 KB
  130. OnlineFood.ipynb1.0 MB
  131. onlinefoods.xlsx - onlinefoods.csv21.2 KB
  132. Restaurant_revenue (1).csv88.3 KB
  133. Resutrants.ipynb2.0 MB
  134. 72 - 11-results.pdf170.9 KB
  135. 72 - Understanding The Results Of Classification Models.mp467.0 MB
  136. 73 - 12-steps.pdf148.1 KB
  137. 73 - Summary Of The Three Models.mp435.6 MB
  138. 74 - The Final Exercise.html1.8 KB
  139. 74 - weekly.csv60.1 KB
  140. 75 - New Ai Features In Python The Latest Updates You Must Know.html4.6 KB
  141. 68 - 09-KNN.pdf236.7 KB
  142. 68 - Knearest Neighbors Classifier.mp4120.4 MB
  143. 69 - Knearest Neighbors In Python Part 1.mp456.2 MB
  144. 70 - Knearest Neighbors In Python Part 2.mp464.4 MB
  145. 71 - Project Exercise 12.html204 bytes
  146. 10_Test_Train.pdf238.7 KB
  147. 11_results.pdf170.9 KB
  148. 12_steps.pdf148.1 KB
  149. Python_CrashC1.ipynb29.6 KB
  150. Python_cc2.ipynb169.5 KB
  151. Product.txt139.5 KB

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