Hands-on ensemble learning with Python : build highly optimized ensemble machine learning models using scikit-learn and Keras /

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Combine popular machine learning techniques to create ensemble models using Python Key Features Implement ensemble models using algorithms such as random forests and AdaBoost Apply boosting, bagging, and stacking ensemble methods to improve the prediction accuracy of your model Explore real-world da...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Kyriadides, George (Autor), Margaritis, Konstantinos G. (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, UK : Packt Publishing, 2019.
Temas:
Python (Computer program language)
Machine learning.
Python (Langage de programmation)
Apprentissage automatique.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • Chapter 1: A Machine Learning Refresher
  • Chapter 2: Getting Started with Ensemble Learning
  • Chapter 3: Voting
  • Chapter 4: Stacking
  • Chapter 5: Bagging
  • Chapter 6: Boosting
  • Chapter 7: Random Forests
  • Chapter 8: Clustering
  • Chapter 9: Classifying Fraudulent Transactions
  • Chapter 10: Predicting Bitcoin Prices
  • Chapter 11: Evaluating Sentiment on Twitter
  • Chapter 12: Recommending Movies with Keras
  • Chapter 13: Clustering World Happiness.

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