Supervised and Unsupervised Data Engineering for Multimedia Data - Tapa dura

Acerca del autor

Suman Kumar Swarnkar, PhD, holds a PhD in computer science and engineering and combines over two years of industry experience with over eight years as an assistant professor.

J. P. Patra, PhD, a seasoned professor, boasts more than 17 years of research and teaching in artificial intelligence, algorithms, cryptography, and network security, with numerous patents and contributions to reputable publishers.

Sapna Singh Kshatri, PhD, serves as an assistant professor specializing in artificial intelligence and machine learning, having authored several books and received multiple awards.

Yogesh Kumar Rathore, an assistant professor with 16 years of experience, has published over 40 research papers in conferences and journals, showcasing a comprehensive understanding of computer science and engineering.

Tien Anh Tran, PhD, is an assistant professor at Vietnam Maritime University, Haiphong, Vietnam. He has almost ten years of research and teaching experience and has published numerous papers in scientific and scholarly journals. He has also been a guest editor and reviewer for several journals.

De la contraportada

Explore the cutting-edge realms of data engineering in multimedia with Supervised and Unsupervised Data Engineering for Multimedia Data, where expert contributors delve into innovative methodologies, offering invaluable insights to empower both novices and seasoned professionals in mastering the art of manipulating multimedia data with precision and efficiency.

Supervised and Unsupervised Data Engineering for Multimedia Data presents a groundbreaking exploration into the intricacies of handling multimedia data through the lenses of both supervised and unsupervised data engineering. Authored by a team of accomplished experts in the field, this comprehensive volume serves as a go-to resource for data scientists, computer scientists, and researchers seeking a profound understanding of cutting-edge methodologies.

The book seamlessly integrates theoretical foundations with practical applications, offering a cohesive framework for navigating the complexities of multimedia data. Readers will delve into a spectrum of topics, including artificial intelligence, machine learning, and data analysis, all tailored to the challenges and opportunities presented by multimedia datasets. From foundational principles to advanced techniques, each chapter provides valuable insights, making this book an essential guide for academia and industry professionals alike. Whether you’re a seasoned practitioner or a newcomer to the field, Supervised and Unsupervised Data Engineering for Multimedia Data illuminates the path toward mastery in manipulating and extracting meaningful insights from multimedia data in the modern age.