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Machine Learning and Interpretation in Neuroimaging

This book constitutes the revised selected papers from the 4th International Workshop on Machine Learning and Interpretation;

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Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology

in both developing new machine learning methods and applications of existing methods to solve challenging problems in clinical neuroimaging;

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Artificial Intelligence and Machine Learning , An Issue of Neuroimaging Clinics of North America

This issue of Neuroimaging Clinics of North America focuses on Artificial Intelligence and Machine Learning and is edited by Dr. Reza;

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Medical Image Computing and Computer Assisted Intervention - MICCAI 2021

learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning;

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OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging

. They focus on addressing the problems of applying machine learning to large and multi-site clinical neuroimaging datasets. The workshop aimed;

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Machine Learning

Machine Learning is an area of artificial intelligence involving the development of algorithms to discover trends and patterns;

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Applied Machine Learning for Smart Data Analysis

The book focuses on how machine learning and the Internet of Things (IoT) has empowered the advancement of information driven arrangements;

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Introduction to Machine Learning and Bioinformatics

Lucidly Integrates Current Activities Focusing on both fundamentals and recent advances, Introduction to Machine Learning and;

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Introduction to Machine Learning and Bioinformatics

Lucidly Integrates Current Activities Focusing on both fundamentals and recent advances, Introduction to Machine Learning and;

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Interpretable Machine Learning

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you;

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Information Management and Machine Intelligence

of topics, including data analytics; AI; machine and deep learning; information management, security, processing techniques and interpretation;

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Practical Machine Learning with Python

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world;

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Neuroinflammation in Vascular Dementia

neuroimaging methods Discusses established and developing treatment strategies Identifies future directions, such as machine learning;

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Machine Interpretation Of Patterns

in various areas of pattern recognition, image processing, machine learning, soft computing, data mining and web intelligence.Machine Interpretation;

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Deep Learning Techniques for IoT Security and Privacy

comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and;

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Machine Learning in the Oil and Gas Industry

Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the;

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Machine Learning in the Oil and Gas Industry

Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the;

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Proceedings of the Second International Conference on Information Management and

interpretation; applications of artificial intelligence in soft computing and pattern recognition; cloud-based applications for machine learning;

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Functional Connectivity, An Issue of Neuroimaging Clinics of North America

This issue of Neuroimaging Clinics of North America focuses on Functional Connectivity, and is edited by Dr. Jay Pillai. Articles will;

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Signal Processing and Machine Learning for Biomedical Big Data

alternate therapies, drugs, and diagnostic tools. Signal Processing and Machine Learning for Biomedical Big Data thus discusses modalities; the;

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Hands-On Machine Learning with R

learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed;

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Machine Learning for Knowledge Discovery with R

Machine Learning for Knowledge Discovery with R contains methodologies and examples for statistical modelling, inference, and prediction;

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Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track

networks; interpretation, explainability, transparency, safety. Part III: Generative models; search and optimization; supervised learning;

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Machine Learning and Knowledge Discovery in Databases. Research Track

networks; interpretation, explainability, transparency, safety. Part III: Generative models; search and optimization; supervised learning;

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Machine Learning Techniques for Improved Business Analytics

of interpretation is important in improving data preparation, analysis, and implementation processes in business organizations. Machine Learning;

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Machine Learning Techniques for Improved Business Analytics

of interpretation is important in improving data preparation, analysis, and implementation processes in business organizations. Machine Learning;

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Deep Learning through Sparse and Low-Rank Modeling

analytic tools to guide the design and interpretation of deep learning models. The development of the theory and models is supported by a wide;

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