Supervised Machine Learning: Optimization Framework and Applications with SAS and R - Tapa blanda

Kolosova, Tanya; Berestizhevsky, Samuel

 
9780367538828: Supervised Machine Learning: Optimization Framework and Applications with SAS and R
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ISBN 10: 0367538822 ISBN 13: 9780367538828
Editorial: Chapman and Hall/CRC, 2022

Sinopsis

AI framework intended to solve a problem of bias-variance tradeoff for supervised learning methods in real-life applications. It comprises of bootstrapping to create multiple training and testing data sets, design and analysis of statistical experiments and optimal hyper-parameters for ML methods.

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Acerca del autor

Tanya Kolosova is a statistician, software engineer, an educator, and a co-author of two books on statistical analysis and metadata-based applications development using SAS. Tanya is an actionable analytics expert, she has extensive knowledge of software development methods and technologies, artificial intelligence methods and algorithms, and statistically designed experiments.

Samuel Berestizhevsky is a statistician, researcher and software engineer. Together with Tanya, Samuel co-authored two books on statistical analysis and metadata-based applications development using SAS. Samuel is an innovator and an expert in the area of automated actionable analytics and artificial intelligence solutions. His extensive knowledge of software development methods, technologies and algorithms allows him to develop solutions on the cutting edge of science.

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Editorial
Chapman and Hall/CRC
Año de publicación
2022
Idioma
Inglés
ISBN 10 
0367538822
ISBN 13 
9780367538828
Encuadernación
Tapa blanda
Número de edición
1
Número de páginas
182
Contacto del fabricante
no disponible
Persona responsable
no disponible

Otras ediciones populares con el mismo título

9780367277321: Supervised Machine Learning: Optimization Framework and Applications with SAS and R

Edición Destacada

ISBN 10:  0367277328 ISBN 13:  9780367277321
Editorial: Chapman and Hall/CRC, 2020
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