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Deep Learning for Data Analytics

of domains including data science, data analytics and biomedical engineering. Deep Learning for Data Analytics: Foundations, Biomedical Applications;

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Machine Learning and Big Data Analytics Paradigms

many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for;

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Deep Learning Techniques and Optimization Strategies in Big Data Analytics

industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear;

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Data Analytics in Biomedical Engineering and Healthcare

medical research scientists. The book covers health analytics, data science, and machine and deep learning applications for biomedical data;

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Intelligent Data-Analytics for Condition Monitoring

Intelligent Data-Analytics for Condition Monitoring: Smart Grid Applications looks at intelligent and meaningful uses of data required;

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Deep Learning in Data Analytics

, graphs, and tables in guiding researchers through deep learning in data science and its applications for society. Deep learning approaches;

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Deep Data Analytics for New Product Development

This book presents and develops the deep data analytics for providing the information needed for successful new product development;

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Deep Data Analytics for New Product Development

This book presents and develops the deep data analytics for providing the information needed for successful new product development;

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Deep Learning and Edge Computing Solutions for High Performance Computing

This book provides an insight into ways of inculcating the need for applying mobile edge data analytics in bioinformatics and medicine. The;

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Advanced Deep Learning Applications in Big Data Analytics

major issue in today's digital world. Advanced Deep Learning Applications in Big Data Analytics is a pivotal reference source that aims to;

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Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization;

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Advanced Data Analytics Using Python

learning Use cloud platforms like GCP and AWS in data analytics Understand Covers design patterns in Python Who This Book Is For Data;

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Advanced Data Analytics Using Python

learning Use cloud platforms like GCP and AWS in data analytics Understand Covers design patterns in Python Who This Book Is For Data scientists;

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Robust Representation for Data Analytics

for Data Analytics covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition;

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Heterogeneous Data Management, Polystores, and Analytics for Healthcare

organized in topical sections as follows: Privacy, Security and/or Policy Issues for Heterogenous Data; COVID-19 Data Analytics and Visualization;

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Fundamentals of Machine Learning for Predictive Data Analytics

introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics;

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Codeless Deep Learning with KNIME

book is forThis book is for data analysts, data scientists, and deep learning developers who are not well-versed in Python but want to learn;

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Applications of Machine Learning in Big-Data Analytics and Cloud Computing

the vast quantities of data. In Cloud and Big Data Analytics, the two areas of Swarm Intelligence and Deep Learning are a developing type;

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Data Science Solutions with Python

learning is unpacked. This book is for intermediate-level data scientists and machine learning engineers who want to learn how to apply key;

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Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches

and deep learning approaches, presents data analytics and mining for decision-support applications, and includes case-based reasoning, natural;

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Applied Data Analytics

algorithms for handling very lage data sizes. Analysis of x-ray images in medical applications, cyber security data, crime data, telecommunications;

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Machine Learning for Subsurface Characterization

Machine Learning for Subsurface Characterization develops and applies neural networks, random forests, deep learning, unsupervised learning;

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Cloud Analytics with Microsoft Azure

insights from your data. You'll explore the power of data with big data analytics, the Internet of Things (IoT), machine learning, artificial;

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Soft Computing in Data Science

organized in topical sections on information and customer analytics; visual data science; machine and deep learning; big data analytics;

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Trends in Deep Learning Methodologies

predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive;

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Big-Data Analytics for Cloud, IoT and Cognitive Computing

describe a practical approach integrating big-data theories, cloud design principles, Internet of Things (IoT) sensing, machine learning, data;

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Advances on Smart and Soft Computing

, big data analytics, smart computing, smart cities, Internet of things (IoT), data communication, cloud computing, machine learning algorithms;

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