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Chapter 1  Ensemble methods Hype or hallelujah Ensemble Methods for Machine Learning, Video Edition.mp4 (23.03 MB)
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Chapter 1  Fit vs  complexity in individual models Ensemble Methods for Machine Learning, Video Edition.mp4 (42.11 MB)
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Chapter 1  Our first ensemble Ensemble Methods for Machine Learning, Video Edition.mp4 (14.49 MB)
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Chapter 1  Summary Ensemble Methods for Machine Learning, Video Edition.mp4 (2.96 MB)
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Chapter 1  Terminology and taxonomy for ensemble methods Ensemble Methods for Machine Learning, Video Edition.mp4 (11.42 MB)
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Chapter 1  Why you should care about ensemble learning Ensemble Methods for Machine Learning, Video Edition.mp4 (16.95 MB)
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Chapter 2  Bagging Bootstrap aggregating Ensemble Methods for Machine Learning, Video Edition.mp4 (41.9 MB)
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Chapter 2  Case study Breast cancer diagnosis Ensemble Methods for Machine Learning, Video Edition.mp4 (29.63 MB)
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Chapter 2  Homogeneous parallel ensembles Bagging and random forests Ensemble Methods for Machine Learning, Video Edition.mp4 (14.96 MB)
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Chapter 2  More homogeneous parallel ensembles Ensemble Methods for Machine Learning, Video Edition.mp4 (16.18 MB)
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Chapter 2  Random forests Ensemble Methods for Machine Learning, Video Edition.mp4 (22.32 MB)
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Chapter 2  Summary Ensemble Methods for Machine Learning, Video Edition.mp4 (5.34 MB)
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Chapter 3  Case study Sentiment analysi Ensemble Methods for Machine Learning, Video Edition.mp4 (37.88 MB)
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Chapter 3  Combining predictions by meta-learning Ensemble Methods for Machine Learning, Video Edition.mp4 (35.21 MB)
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Chapter 3  Combining predictions by weighting Ensemble Methods for Machine Learning, Video Edition.mp4 (42.25 MB)
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Chapter 3  Heterogeneous parallel ensembles Combining strong learners Ensemble Methods for Machine Learning, Video Edition.mp4 (38.37 MB)
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Chapter 3  Summary Ensemble Methods for Machine Learning, Video Edition.mp4 (7.68 MB)
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Chapter 4  AdaBoost Adaptive boosting Ensemble Methods for Machine Learning, Video Edition.mp4 (51.51 MB)
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Chapter 4  AdaBoost in practice Ensemble Methods for Machine Learning, Video Edition.mp4 (21.11 MB)
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Chapter 4  Case study Handwritten digit classification Ensemble Methods for Machine Learning, Video Edition.mp4 (19.79 MB)
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Chapter 4  LogitBoost Boosting with the logistic loss Ensemble Methods for Machine Learning, Video Edition.mp4 (14.52 MB)
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Chapter 4  Sequential ensembles Adaptive boosting Ensemble Methods for Machine Learning, Video Edition.mp4 (18.08 MB)
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Chapter 4  Summary Ensemble Methods for Machine Learning, Video Edition.mp4 (4.55 MB)
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Chapter 5  Case study Document retrieval Ensemble Methods for Machine Learning, Video Edition.mp4 (23.31 MB)
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Chapter 5  Gradient boosting Gradient descent + boosting Ensemble Methods for Machine Learning, Video Edition.mp4 (56.03 MB)
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Chapter 5  LightGBM A framework for gradient boosting Ensemble Methods for Machine Learning, Video Edition.mp4 (23.36 MB)
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Chapter 5  LightGBM in practice Ensemble Methods for Machine Learning, Video Edition.mp4 (43.41 MB)
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Chapter 5  Sequential ensembles Gradient boosting Ensemble Methods for Machine Learning, Video Edition.mp4 (61.36 MB)
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Chapter 5  Summary Ensemble Methods for Machine Learning, Video Edition.mp4 (5.44 MB)
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Chapter 6  Case study redux Document retrieval Ensemble Methods for Machine Learning, Video Edition.mp4 (17.26 MB)
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Chapter 6  Newton boosting Newton's method + boosting Ensemble Methods for Machine Learning, Video Edition.mp4 (41.72 MB)
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Chapter 6  Sequential ensembles Newton boosting Ensemble Methods for Machine Learning, Video Edition.mp4 (50.42 MB)
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Chapter 6  Summary Ensemble Methods for Machine Learning, Video Edition.mp4 (6.57 MB)
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Chapter 6  XGBoost A framework for Newton boosting Ensemble Methods for Machine Learning, Video Edition.mp4 (25.39 MB)
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Chapter 6  XGBoost in practice Ensemble Methods for Machine Learning, Video Edition.mp4 (15.96 MB)
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Chapter 7  Case study Demand forecasting Ensemble Methods for Machine Learning, Video Edition.mp4 (48.15 MB)
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Chapter 7  Learning with continuous and count labels Ensemble Methods for Machine Learning, Video Edition.mp4 (91.72 MB)
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Chapter 7  Parallel ensembles for regression Ensemble Methods for Machine Learning, Video Edition.mp4 (35.29 MB)
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Chapter 7  Sequential ensembles for regression Ensemble Methods for Machine Learning, Video Edition.mp4 (36.9 MB)
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Chapter 7  Summary Ensemble Methods for Machine Learning, Video Edition.mp4 (7.37 MB)
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Chapter 8  Case study Income prediction Ensemble Methods for Machine Learning, Video Edition.mp4 (36.92 MB)
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Chapter 8  CatBoost A framework for ordered boosting Ensemble Methods for Machine Learning, Video Edition.mp4 (27.16 MB)
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Chapter 8  Encoding high-cardinality string features Ensemble Methods for Machine Learning, Video Edition.mp4 (21.97 MB)
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Chapter 8  Learning with categorical features Ensemble Methods for Machine Learning, Video Edition.mp4 (72.47 MB)
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Chapter 8  Summary Ensemble Methods for Machine Learning, Video Edition.mp4 (10.42 MB)
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Chapter 9  Black-box methods for global explainability Ensemble Methods for Machine Learning, Video Edition.mp4 (48.71 MB)
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Chapter 9  Black-box methods for local explainability Ensemble Methods for Machine Learning, Video Edition.mp4 (62.46 MB)
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Chapter 9  Case study Data-driven marketing Ensemble Methods for Machine Learning, Video Edition.mp4 (19.37 MB)
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Chapter 9  Explaining your ensembles Ensemble Methods for Machine Learning, Video Edition.mp4 (50.97 MB)
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Chapter 9  Glass-box ensembles Training for interpretability Ensemble Methods for Machine Learning, Video Edition.mp4 (36.73 MB)
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Chapter 9  Summary Ensemble Methods for Machine Learning, Video Edition.mp4 (14.74 MB)
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Epilogue Ensemble Methods for Machine Learning, Video Edition.mp4 (25.12 MB)
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Part 1  The basics of ensembles Ensemble Methods for Machine Learning, Video Edition.mp4 (2.61 MB)
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Part 2 Essential ensemble methods Ensemble Methods for Machine Learning, Video Edition.mp4 (4.43 MB)
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Part 3  Ensembles in the wild Adapting ensemble methods to your data Ensemble Methods for Machine Learning, Video Edition.mp4 (7.28 MB)
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