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Causal Inference and Discovery in Python : Unlock the Secrets of Modern Causal Machine Learning with Dowhy, EconML, Pytorch and More /
Demystify causal inference and casual discovery by uncovering causal principles and merging them with powerful machine learning algorithms for observational and experimental data Purchase of the print or Kindle book includes a free PDF eBook Key Features Examine Pearlian causal concepts such as stru...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing,
[2023]
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Table of ContentsCausality
- Hey, We Have Machine Learning, So Why Even Bother?Judea Pearl and the Ladder of CausationRegression, Observations, and InterventionsGraphical ModelsForks, Chains, and ImmoralitiesNodes, Edges, and Statistical (In)dependenceThe Four-Step Process of Causal InferenceCausal Models
- Assumptions and ChallengesCausal Inference and Machine Learning
- from Matching to Meta-LearnersCausal Inference and Machine Learning
- Advanced Estimators, Experiments, Evaluations, and MoreCausal Inference and Machine Learning
- Deep Learning, NLP, and BeyondCan I Have a Causal Graph, Please?Causal Discovery and Machine Learning
- from Assumptions to ApplicationsCausal Discovery and Machine Learning
- Advanced Deep Learning and BeyondEpilogue.