Fusion of Machine Learning Paradigms: Theory and Applications 9783031223716, 9783031223709, 3031223713

Information Fusion: Machine Learning Methods 981168975X, 9789811689758

In the big data era, increasing information can be extracted from the same source object or scene. For instance, a perso

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Metaheuristics in Machine Learning: Theory and Applications 9783030705428

410 101 111MB Read more

Machine Learning Paradigms: Advances in Deep Learning-based Technological Applications [1st ed.] 9783030497231, 9783030497248

At the dawn of the 4th Industrial Revolution, the field of Deep Learning (a sub-field of Artificial Intelligence and Mac

611 35 15MB Read more

Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges [1st ed. 2021] 3030593371, 9783030593377

This book is intended to present the state of the art in research on machine learning and big data analytics. The accept

1,886 112 24MB Read more

Data Science Fusion: Integrating Maths, Python, and Machine Learning

In this book, we will explore in the world of Data Science and inside you will gain informative insights in depth. You w

110 44 1MB Read more

Machine Learning Algorithms and Applications 9781119768852

515 123 13MB Read more

Novel Financial Applications of Machine Learning and Deep Learning: Algorithms, Product Modeling, and Applications 303118551X, 9783031185519

This book presents the state-of-the-art applications of machine learning in the finance domain with a focus on financial

341 48 6MB Read more

Linear Algebra And Optimization With Applications To Machine Learning - Volume II: Fundamentals of Optimization Theory with Applications to Machine Learning [2] 9789811216565, 9789811216572, 9789811216589

Volume 2 applies the linear algebra concepts presented in Volume 1 to optimization problems which frequently occur throu

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Fundamentals of optimization theory with applications to machine learning [draft ed.]

650 66 7MB Read more

Fundamentals of optimization theory with applications to machine learning [draft ed.]

569 97 6MB Read more