Ensemble Learning for AI Developers : Learn Bagging, Stacking, and Boosting Methods with Use Cases

Ensemble Learning for AI Developers Learn Bagging, Stacking, and Boosting Methods with Use Cases

Use ensemble learning techniques and models to improve your machine learning results. Ensemble Learning for AI Developers starts you at the beginning with an historical overview and explains key ensemble techniques and why they are needed. You then will learn how to change training data using baggin...

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Detalles Bibliográficos
Autores principales: Kumar, Alok. author (author), Jain, Mayank. author
Formato: Libro electrónico
Idioma:Inglés
Publicado: Berkeley, CA : Apress 2020.
Edición:1st ed. 2020.
Materias:
Artificial intelligence.
Python (Computer program language).
Open source software.
Computer programming.
Artificial Intelligence.
Python.
Open Source.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630916906719
Tabla de Contenidos:
  • Chapter 1: Why Ensemble Techniques Are Needed
  • Chapter 2: Mix Training Data
  • Chapter 3: Mix Models
  • Chapter 4: Mix Combinations
  • Chapter 5: Use Ensemble Learning Libraries
  • Chapter 6: Tips and Best Practices.-.

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