Téléchargez le livre : Ensemble Learning for AI Developers

Ensemble Learning for AI Developers

Learn Bagging, Stacking, and Boosting Methods with Use Cases

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Éditeur :

Apress


Paru le : 2020-06-18



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Description
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 bagging, bootstrap aggregating, random forest models, and cross-validation methods. Authors Kumar and Jain provide best practices to guide you in combining models and using tools to boost performance of your machine learning projects. They teach you how to effectively implement ensemble concepts such as stacking and boosting and to utilize popular libraries such as Keras, Scikit Learn, TensorFlow, PyTorch, and Microsoft LightGBM. Tips are presented to apply ensemble learning in different data science problems, including time series data, imaging data, and NLP. Recent advances in ensemble learning are discussed. Sample code is provided in the form of scripts and the IPython notebook.



What You Will Learn
Understand the techniques and methods utilized in ensemble learningUse bagging, stacking, and boosting to improve performance of your machine learning projects by combining models to decrease variance, improve predictions, and reduce biasEnhance your machine learning architecture with ensemble learning




Who This Book Is For
Data scientists and machine learning engineers keen on exploring ensemble learning
Pages
136 pages
Collection
n.c
Parution
2020-06-18
Marque
Apress
EAN papier
9781484259399
EAN PDF
9781484259405
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
13
Taille du fichier
3308 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
52,24 €
EAN EPUB
9781484259405
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
13
Taille du fichier
3103 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
52,24 €

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