Pallavi Chavan – författare

Essentials of Big Data Analytics: Applications in R and Python is a comprehensive guide that demystifies the complex world of big data analytics, blending theoretical concepts with hands-on practices using the Python and R programming languages and MapReduce framework. This book bridges the gap between theory and practical implementation, providing clear and practical understanding of the key principles and techniques essential for harnessing the power of big data. Essentials of Big Data Analytics is designed to provide a comprehensive resource for readers looking to deepen their understanding of Big Data analytics, particularly within a computer science, engineering, and data science context. By bridging theoretical concepts with practical applications, the book emphasizes hands-on learning through exercises and tutorials, specifically utilizing R and Python. Given the growing role of Big Data in industry and scientific research, this book serves as a timely resource to equip professionals with the skills needed to thrive in data-driven environments.Includes hands-on Tutorials and Case Studies: Structured exercises and real-world examples reinforce learning and skill-buildingFocuses on Python and R for Big Data: Detailed lessons in Python and R programming cater to the increasing demand for data science expertiseBalanced Theory and Practice: Comprehensive coverage ensures a strong theoretical foundation paired with actionable insights for real-world application

Essentials of Big Data Analytics: Applications in R and Python is a comprehensive guide that demystifies the complex world of big data analytics, blending theoretical concepts with hands-on practices using the Python and R programming languages and MapReduce framework. This book bridges the gap between theory and practical implementation, providing clear and practical understanding of the key principles and techniques essential for harnessing the power of big data. Essentials of Big Data Analytics is designed to provide a comprehensive resource for readers looking to deepen their understanding of Big Data analytics, particularly within a computer science, engineering, and data science context. By bridging theoretical concepts with practical applications, the book emphasizes hands-on learning through exercises and tutorials, specifically utilizing R and Python. Given the growing role of Big Data in industry and scientific research, this book serves as a timely resource to equip professionals with the skills needed to thrive in data-driven environments. - Includes hands-on Tutorials and Case Studies: Structured exercises and real-world examples reinforce learning and skill-building- Focuses on Python and R for Big Data: Detailed lessons in Python and R programming cater to the increasing demand for data science expertise- Balanced Theory and Practice: Comprehensive coverage ensures a strong theoretical foundation paired with actionable insights for real-world application

Quantum Cryptography and Secure Communications: An Applied Approach explores the fundamentals of quantum computing, quantum cryptography, and secure communication, and offers an insight into quantum key distribution (QKD) and Post-Quantum Cryptography (PQC). The book looks at QKD protocols, techniques and algorithms, such as BB84, E91 and SARG04, and how secure communication uses quantum physics to construct a cryptographic protocol which allows two parties to generate a shared secret key that is known only to them. The applied approach of the book examines recent implementations of quantum cryptography for secure communication among different industry vertices, discusses algorithms which are quantum resistant, such as lattice based and code based algorithms, and considers how secure quantum computing applications addresses societal challenges such as sustainability, as well as the crucial role played by simulations. Quantum Cryptography and Secure Communications finishes with a study of current research trends and uses cases within quantum cryptography to provide a structured learning process that intertwines theory with practical applications, to make quantum cryptography more approachable and relevant.Offers an overview of the fields of quantum cryptography and secure communicationsCombines quantum key distribution (QKD) and post-quantum cryptography techniquesProvides examples and case studies to ground the theory in practiceConsiders how quantum computing applications can address sustainability and societal challenges