Computer Books › machine learning an algorithmic perspective

Data-Driven Modeling of Cyber-Physical Systems Using Side-Channel Analysis (Hardcover)

This book provides a new perspective on modeling cyber-physical systems (CPS) using a data-driven approach. The authors cover the use of state-of-the-art machine learning and artificial intelligence algorithms for modeling various aspect of the CPS.... more

Advances in Computer Vision and Pattern Recognition: Compression Schemes for Mining Large Datasets: A Machine Learning Perspective (Hardcover)

This book addresses the challenges of data abstraction generation using a least number of database scans compressing data through novel lossy and non-lossy schemes and carrying out clustering and classification directly in the compressed domain.... more

Ai Machine Learning and Deep Learning: A Security Perspective (Hardcover)

Today Artificial Intelligence (AI) and Machine Learning/ Deep Learning (ML/DL) have become the hottest areas in information technology. In our society many intelligent devices rely on AI/ML/DL algorithms/tools for smart operations. Although AI/ML/DL... more

AI for Big Data-Based Engineering Applications from Security Perspectives (Hardcover)

Artificial intelligence (AI) machine learning and advanced electronic circuits involve learning from every data input and using those inputs to generate new rules for future business analytics. AI and machine learning are now giving us new... more

Artificial Intelligence Machine Learning and Deep Learning in Precision Medicine in Liver Diseases: Concept Technolog (Paperback)

Artificial Intelligence Machine Learning and Deep Learning in Precision Medicine and Liver Diseases: Concept Technology Application and Perspectives combines four major applications of artificial intelligence (AI) within the field of clinical... more

Algorithmic Aspects of Machine Learning (Paperback)

This book bridges theoretical computer science and machine learning by exploring what the two sides can teach each other. It emphasizes the need for flexible tractable models that better capture not what makes machine learning hard but what makes it... more

Innovations in Health Informatics and Healthcare: Artificial Intelligence and Machine Learning: An Intelligent Perspective of Emerging Technologies (Hardcover)

This book focuses on Artificial Intelligence and Machine Learning technologies and how they are progressively being incorporated into a wide range of products including consumer gadgets smart personal assistants cutting-edge medical diagnostic... more

Data Analytics in Bioinformatics: A Machine Learning Perspective (Hardcover)

Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences gene and protein... more

Adaptive Computation and Machine Learning series: Machine Learning : A Probabilistic Perspective (Hardcover)

A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach. Today s Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these... more

Adaptation Learning and Optimization: Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition (Hardcover)

This book explores multidimensional particle swarm optimization a technique developed by the authors and presented in a well-defined algorithmic approach. All featured applications are supported with fully documented source code as well as sample... more

Machine Learning: A Theoretical Approach (Hardcover)

This is the first comprehensive introduction to computational learning theory. The author s uniform presentation of fundamental results and their applications offers AI researchers a theoretical perspective on the problems they study. The book... more

Foundations of Data Science (Hardcover)

This book provides an introduction to the mathematical and algorithmic foundations of data science including machine learning high-dimensional geometry and analysis of large networks. Topics include the counterintuitive nature of data in high... more