Python for Renewable Energy Applications
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Sprache:Englisch
97,01 €
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
ePUB
Kopierschutz
Nein
Family Sharing
Nein
Text-to-Speech
Ja
Erscheinungsdatum
04.10.2024
Verlag
Abdellatif M. SadeqSeitenzahl
(Printausgabe)
Dateigröße
5116 KB
Sprache
Englisch
EAN
9798990783669
This book serves as a comprehensive guide for individuals interested in applying Python programming to solve challenges in renewable energy systems. It offers a structured learning experience, starting from the basics of Python programming and progressing to more advanced applications in data management, modeling, and optimization. The book emphasizes hands-on learning, providing readers with practical examples and case studies that illustrate the role of Python in analyzing and optimizing various renewable energy systems, such as solar, wind, and biomass.
Throughout the book, readers will explore key Python libraries that are essential for numerical analysis and data manipulation, such as NumPy, pandas, and matplotlib. These libraries enable users to handle complex data and perform tasks such as data cleaning, visualization, and statistical analysis. Additionally, the book delves into the use of machine learning and predictive modeling to enhance the efficiency and sustainability of renewable energy systems, providing readers with tools to analyze and forecast energy production trends.
Ultimately, this book aims to equip engineers, researchers, and students with the skills to leverage Python in real-world renewable energy applications. It is designed to be accessible to both beginners in Python and experienced professionals in the renewable energy field, making it a valuable resource for anyone looking to contribute to the global shift towards sustainable energy solutions.
Throughout the book, readers will explore key Python libraries that are essential for numerical analysis and data manipulation, such as NumPy, pandas, and matplotlib. These libraries enable users to handle complex data and perform tasks such as data cleaning, visualization, and statistical analysis. Additionally, the book delves into the use of machine learning and predictive modeling to enhance the efficiency and sustainability of renewable energy systems, providing readers with tools to analyze and forecast energy production trends.
Ultimately, this book aims to equip engineers, researchers, and students with the skills to leverage Python in real-world renewable energy applications. It is designed to be accessible to both beginners in Python and experienced professionals in the renewable energy field, making it a valuable resource for anyone looking to contribute to the global shift towards sustainable energy solutions.
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