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About the Module 3. Hyperparameter tuning category
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1
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2
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29 January 2021
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Learning_rate=1 vs CV=2
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3
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21
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21 July 2021
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Cross-validation and hyperparameter tuning
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1
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28
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14 July 2021
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Test score greater than train score
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1
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16
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14 July 2021
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Small typo in M3.02 exercice
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6
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28
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10 July 2021
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Pipeline or make_pipeline + grid searchCV
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7
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29
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29 June 2021
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Another confusion about terminology: logistic regression or logistic classification
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3
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31
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25 June 2021
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Loguniform
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3
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16
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25 June 2021
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Parallel coordinates plot?
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1
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27
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23 June 2021
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In Notebook (Set and Get Hyperparameters)
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1
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17
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22 June 2021
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Manual Tuning (small typo)
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1
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11
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22 June 2021
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Code in Solution Throwing Error,
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2
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20
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22 June 2021
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Module 3 (Hyperparameter): Overview (clarify)
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7
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19
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22 June 2021
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The rationale behind nested cross-validation
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4
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56
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21 June 2021
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Logisitic regression is a method of classifying?
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1
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14
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21 June 2021
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Question on Wrap-Up Quiz 3
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12
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81
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21 June 2021
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Why I obtained different results than you and other in the GridSearchCV?
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2
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37
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20 June 2021
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Different solution M3.01?
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10
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79
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16 June 2021
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Exercise M3.02
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2
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39
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16 June 2021
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M3-Lecture-Test / Train / Cross Validation
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4
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34
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16 June 2021
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Question on Automated Tuning lecture
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1
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25
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15 June 2021
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Why was there a [1] next to rsplit()?
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5
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23
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14 June 2021
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Summary for lecture - Hyperparameter tuning by grid-search
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1
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22
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14 June 2021
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Why create the class loguniform_int and not just use loguniform.rvs(a, b, size=n).astype(int)?
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4
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15
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14 June 2021
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2 small typos in the "Hyperparameter tuning by randomized-search" lesson?
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1
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18
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14 June 2021
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Hyperparameters
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3
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64
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14 June 2021
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Failure to Run Sandbox and Standalone Script
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1
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13
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12 June 2021
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Gridsearch mith multi preprocessors
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1
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16
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12 June 2021
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Pipeline or make_pipeline?
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3
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14
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11 June 2021
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Q3 - Answer B
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4
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52
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11 June 2021
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