Ensemble Methods for Machine Learning, Video Edition
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11:05:24
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Chapter 1. Ensemble methods Hype or hallelujah Ensemble Methods for Machine Learning, Video Edition.mp4
09:28
Chapter 1. Fit vs. complexity in individual models Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 1. Our first ensemble Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 1. Summary Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 1. Terminology and taxonomy for ensemble methods Ensemble Methods for Machine Learning, Video Edition.mp4
03:51
Chapter 1. Why you should care about ensemble learning Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 2. Bagging Bootstrap aggregating Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 2. Case study Breast cancer diagnosis Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 2. Homogeneous parallel ensembles Bagging and random forests Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 2. More homogeneous parallel ensembles Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 2. Random forests Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 2. Summary Ensemble Methods for Machine Learning, Video Edition.mp4
01:58
Chapter 3. Case study Sentiment analysi Ensemble Methods for Machine Learning, Video Edition.mp4
16:36
Chapter 3. Combining predictions by meta-learning Ensemble Methods for Machine Learning, Video Edition.mp4
15:14
Chapter 3. Combining predictions by weighting Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 3. Heterogeneous parallel ensembles Combining strong learners Ensemble Methods for Machine Learning, Video Edition.mp4
14:57
Chapter 3. Summary Ensemble Methods for Machine Learning, Video Edition.mp4
02:34
Chapter 4. AdaBoost Adaptive boosting Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 4. AdaBoost in practice Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 4. Case study Handwritten digit classification Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 4. LogitBoost Boosting with the logistic loss Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 4. Sequential ensembles Adaptive boosting Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 4. Summary Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 5. Case study Document retrieval Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 5. Gradient boosting Gradient descent + boosting Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 5. LightGBM A framework for gradient boosting Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 5. LightGBM in practice Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 5. Sequential ensembles Gradient boosting Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 5. Summary Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 6. Case study redux Document retrieval Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 6. Newton boosting Newtons method + boosting Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 6. Sequential ensembles Newton boosting Ensemble Methods for Machine Learning, Video Edition.mp4
21:31
Chapter 6. Summary Ensemble Methods for Machine Learning, Video Edition.mp4
02:16
Chapter 6. XGBoost A framework for Newton boosting Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 6. XGBoost in practice Ensemble Methods for Machine Learning, Video Edition.mp4
07:24
Chapter 7. Case study Demand forecasting Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 7. Learning with continuous and count labels Ensemble Methods for Machine Learning, Video Edition.mp4
38:03
Chapter 7. Parallel ensembles for regression Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 7. Sequential ensembles for regression Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 7. Summary Ensemble Methods for Machine Learning, Video Edition.mp4
02:41
Chapter 8. Case study Income prediction Ensemble Methods for Machine Learning, Video Edition.mp4
15:54
Chapter 8. CatBoost A framework for ordered boosting Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 8. Encoding high-cardinality string features Ensemble Methods for Machine Learning, Video Edition.mp4
10:21
Chapter 8. Learning with categorical features Ensemble Methods for Machine Learning, Video Edition.mp4
32:51
Chapter 8. Summary Ensemble Methods for Machine Learning, Video Edition.mp4
03:16
Chapter 9. Black-box methods for global explainability Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 9. Black-box methods for local explainability Ensemble Methods for Machine Learning, Video Edition.mp4
26:41
Chapter 9. Case study Data-driven marketing Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 9. Explaining your ensembles Ensemble Methods for Machine Learning, Video Edition.mp4
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Chapter 9. Glass-box ensembles Training for interpretability Ensemble Methods for Machine Learning, Video Edition.mp4
15:02
Chapter 9. Summary Ensemble Methods for Machine Learning, Video Edition.mp4
04:39
Epilogue Ensemble Methods for Machine Learning, Video Edition.mp4
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Part 1. The basics of ensembles Ensemble Methods for Machine Learning, Video Edition.mp4
01:28
Part 2 Essential ensemble methods Ensemble Methods for Machine Learning, Video Edition.mp4
01:50
Part 3. Ensembles in the wild Adapting ensemble methods to your data Ensemble Methods for Machine Learning, Video Edition.mp4
02:45
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View courses O'ReillyO'Reilly Media is an American learning company established by Tim O'Reilly that publishes books, produces tech conferences, and provides an online learning platform. Its distinctive brand features a woodcut of an animal on many of its book covers.
- language english
- Training sessions 55
- duration 11:05:24
- Release Date 2024/02/10
