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1. Gathering Business Knowledge.mp4
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25.1 MB
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1. Gathering Business Knowledge.vtt
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1. Installing Python and Anaconda.mp4
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18.6 MB
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1. Installing Python and Anaconda.vtt
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2.2 KB
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1. Introduction to Machine Learning.mp4
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123.8 MB
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1. Introduction to Machine Learning.vtt
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16.3 KB
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1. Three Classifiers and the problem statement.mp4
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22.9 MB
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1. Three Classifiers and the problem statement.vtt
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3.3 KB
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1. Types of Data.mp4
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25.9 MB
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1. Types of Data.vtt
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4.3 KB
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1. Welcome to the course!.mp4
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17.6 MB
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1. Welcome to the course!.vtt
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3.3 KB
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1.1 00_Introduction_01_py.pdf.pdf
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472.2 KB
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1.1 01_01_Lecture_TypesOfData.pdf.pdf
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177.7 KB
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1.1 01_INtro.pdf.pdf
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190.4 KB
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1.1 03_01_PDE_Business_knowledge.pdf.pdf
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153.9 KB
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1.1 Lecture_machineLearning.pdf.pdf
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991.6 KB
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10. Confusion Matrix.mp4
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26.7 MB
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10. Confusion Matrix.vtt
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10. Outlier treatment in Python.mp4
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58.4 MB
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10. Outlier treatment in Python.vtt
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7 KB
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10.1 06_Confusion matrix.pdf.pdf
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222.3 KB
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11. Making Confusion Matrix in Python.mp4
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MP4
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64.7 MB
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11. Making Confusion Matrix in Python.vtt
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8.8 KB
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11. Project Exercise 3.html
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HTML
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204.8 B
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12. Evaluating performance of model.mp4
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42.8 MB
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12. Evaluating performance of model.vtt
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7.5 KB
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12. Missing Value Imputation.mp4
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27.6 MB
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12. Missing Value Imputation.vtt
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3.6 KB
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12.1 04_05_PDE_Missing_value.pdf.pdf
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315.7 KB
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12.1 08_ROC.pdf.pdf
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183.1 KB
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13. Evaluating model performance in Python.mp4
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11.8 MB
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13. Evaluating model performance in Python.vtt
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2.1 KB
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13. Missing Value Imputation in Python.mp4
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27.6 MB
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13. Missing Value Imputation in Python.vtt
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3.6 KB
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14. Project Exercise 4.html
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HTML
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204.8 B
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14. Project Exercise 9.html
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204.8 B
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15. Linear Discriminant Analysis.mp4
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48.7 MB
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15. Linear Discriminant Analysis.vtt
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15. Seasonality in Data.mp4
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20.9 MB
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15. Seasonality in Data.vtt
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15.1 04_07_PDE_Seasonality.pdf.pdf
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364.1 KB
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15.1 07_LDA.pdf.pdf
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183.1 KB
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16. LDA in Python.mp4
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14.4 MB
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16. LDA in Python.vtt
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16. Variable Transformation.mp4
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15.3 MB
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16. Variable Transformation.vtt
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16.1 04_07_Variable_Transformation.pdf.pdf
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456.1 KB
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17. Project Exercise 10.html
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204.8 B
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17. Variable transformation and Deletion in Python.mp4
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35.6 MB
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17. Variable transformation and Deletion in Python.vtt
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3.4 KB
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18. Project Exercise 5.html
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204.8 B
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18. Test-Train Split.mp4
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45.7 MB
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18. Test-Train Split.vtt
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18.1 10_Test_Train.pdf.pdf
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238.7 KB
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19. Dummy variable creation Handling qualitative data.mp4
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40.6 MB
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19. Dummy variable creation Handling qualitative data.vtt
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19. Test-Train Split in Python.mp4
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43.1 MB
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19. Test-Train Split in Python.vtt
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19.1 04_11_Dummy_Var.pdf.pdf
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163 KB
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2. Building a Machine Learning model.mp4
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45.3 MB
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2. Building a Machine Learning model.vtt
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2. Data Exploration.mp4
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23.4 MB
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2. Data Exploration.vtt
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2. Opening Jupyter Notebook.mp4
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73.1 MB
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2. Opening Jupyter Notebook.vtt
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8 KB
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2. Types of Statistics.mp4
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13.2 MB
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2. Types of Statistics.vtt
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2. Why can't we use Linear Regression.mp4
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20.4 MB
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2. Why can't we use Linear Regression.vtt
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2.1 01_02_Lecture_TypesOfStatistics.pdf.pdf
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171.7 KB
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2.1 02_whynot_linear.pdf.pdf
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155.3 KB
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2.1 03_02_PDE_Data_exploration.pdf.pdf
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322.9 KB
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20. Dummy variable creation in Python.mp4
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MP4
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33.9 MB
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20. Dummy variable creation in Python.vtt
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4.7 KB
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20. Project Exercise 11.html
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HTML
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204.8 B
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21. K-Nearest Neighbors classifier.mp4
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83.6 MB
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21. K-Nearest Neighbors classifier.vtt
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8.3 KB
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21. Project Exercise 6.html
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204.8 B
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21.1 09_KNN.pdf.pdf
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236.7 KB
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22. K-Nearest Neighbors in Python Part 1.mp4
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45.9 MB
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22. K-Nearest Neighbors in Python Part 1.vtt
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23. K-Nearest Neighbors in Python Part 2.mp4
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52 MB
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23. K-Nearest Neighbors in Python Part 2.vtt
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24. Project Exercise 12.html
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204.8 B
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25. Understanding the results of classification models.mp4
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46 MB
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25. Understanding the results of classification models.vtt
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6.3 KB
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25.1 11_results.pdf.pdf
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170.9 KB
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26. Summary of the three models.mp4
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25.3 MB
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26. Summary of the three models.vtt
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4.8 KB
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26.1 12_steps.pdf.pdf
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148.1 KB
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27. The Final Exercise!.html
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1.8 KB
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28. Course Conclusion.html
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1 KB
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3. Describing data Graphically.mp4
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82.2 MB
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3. Describing data Graphically.vtt
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3. Introduction to Jupyter.mp4
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51.3 MB
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3. Introduction to Jupyter.vtt
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3. Logistic Regression.mp4
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39.1 MB
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3. Logistic Regression.vtt
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3. The Dataset and the Data Dictionary.mp4
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87.6 MB
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3. The Dataset and the Data Dictionary.vtt
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7.5 KB
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3.1 01_03_Lecture_DataSummaryandGraph.pdf.pdf
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317.9 KB
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3.1 03_logistic.pdf.pdf
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352.7 KB
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4. Arithmetic operators in Python Python Basics.mp4
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16 MB
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4. Arithmetic operators in Python Python Basics.vtt
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3.5 KB
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4. Data Import in Python.mp4
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25.5 MB
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4. Data Import in Python.vtt
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4. Measures of Centers.mp4
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45.7 MB
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4. Measures of Centers.vtt
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4. Training a Simple Logistic Model in Python.mp4
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MP4
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61.2 MB
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4. Training a Simple Logistic Model in Python.vtt
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8.6 KB
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4.1 01_04_Lecture_Centers.pdf.pdf
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313 KB
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5. Practice Exercise 1.html
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307.2 B
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5. Project Exercise 1.html
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HTML
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512 B
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5. Project Exercise 7.html
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HTML
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307.2 B
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5. Strings in Python Python Basics.mp4
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80.6 MB
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5. Strings in Python Python Basics.vtt
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14.3 KB
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5.1 Exercise-1.pdf.pdf
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553.8 KB
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5.1 Movie_collection.csv.csv
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55.8 KB
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6. Lists, Tuples and Directories Python Basics.mp4
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73.7 MB
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6. Lists, Tuples and Directories Python Basics.vtt
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14.6 KB
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6. Measures of Dispersion.mp4
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28.4 MB
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6. Measures of Dispersion.vtt
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6. Result of Simple Logistic Regression.mp4
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31.1 MB
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6. Result of Simple Logistic Regression.vtt
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6. Univariate analysis and EDD.mp4
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27.3 MB
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6. Univariate analysis and EDD.vtt
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3.1 KB
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6.1 01_05_Lecture_Dispersion.pdf.pdf
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210.6 KB
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6.1 03_04_PDE_Univariate_Analysis_Uni.pdf.pdf
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333.4 KB
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6.1 04_P_value.pdf.pdf
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228 KB
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7. EDD in Python.mp4
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97.1 MB
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7. EDD in Python.vtt
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14.4 KB
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7. Logistic with multiple predictors.mp4
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MP4
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10 MB
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7. Logistic with multiple predictors.vtt
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2.5 KB
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7. Practice Exercise 2.html
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307.2 B
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7. Working with Numpy Library of Python.mp4
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54.1 MB
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7. Working with Numpy Library of Python.vtt
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9.1 KB
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7.1 05_Multiple_predictors.pdf.pdf
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151.3 KB
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7.1 Exercise-2.pdf.pdf
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469.9 KB
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8. Project Exercise 2.html
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204.8 B
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8. Training multiple predictor Logistic model in Python.mp4
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MP4
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34 MB
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8. Training multiple predictor Logistic model in Python.vtt
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8. Working with Pandas Library of Python.mp4
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MP4
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56.4 MB
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8. Working with Pandas Library of Python.vtt
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7.2 KB
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9. Outlier Treatment.mp4
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MP4
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27.8 MB
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9. Outlier Treatment.vtt
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4 KB
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9. Project Exercise 8.html
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307.2 B
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9. Working with Seaborn Library of Python.mp4
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MP4
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48.9 MB
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9. Working with Seaborn Library of Python.vtt
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6.5 KB
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9.1 04_06_PDE_Outlier_Treatment.pdf.pdf
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355.1 KB
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[CourseClub.Me].url
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[DesireCourse.Net].url
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