Building statistical models in Python : develop useful models for regression, classification, time series, and survival analysis /

The ability to proficiently perform statistical modeling is a fundamental skill for data scientists and essential for businesses reliant on data insights. Building Statistical Models with Python is a comprehensive guide that will empower you to leverage mathematical and statistical principles in dat...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Nguyen, Huy Hoang (Autor), Adams, Paul N. (Autor), Miller, Stuart J. (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, UK : Packt Publishing Ltd., 2023.
Edición:1st edition.
Temas:
Mathematical statistics.
Mathematical models.
Python (Computer program language)
Statistics.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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520 |a The ability to proficiently perform statistical modeling is a fundamental skill for data scientists and essential for businesses reliant on data insights. Building Statistical Models with Python is a comprehensive guide that will empower you to leverage mathematical and statistical principles in data assessment, understanding, and inference generation. This book not only equips you with skills to navigate the complexities of statistical modeling, but also provides practical guidance for immediate implementation through illustrative examples. Through emphasis on application and code examples, you’ll understand the concepts while gaining hands-on experience. With the help of Python and its essential libraries, you’ll explore key statistical models, including hypothesis testing, regression, time series analysis, classification, and more. By the end of this book, you’ll gain fluency in statistical modeling while harnessing the full potential of Python's rich ecosystem for data analysis. 
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