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Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine;

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Practical Machine Learning for Data Analysis Using Python

Practical Machine Learning for Data Analysis Using Python is a problem solver's guide for creating real-world intelligent systems. It;

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Practical Biomedical Signal Analysis Using MATLAB (R)

processing methods and applications, this second edition of Practical Biomedical Signal Analysis Using MATLAB (R) also offers practical guidance on;

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Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their;

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Biomedical Signal Analysis for Connected Healthcare

Biomedical Signal Analysis for Connected Healthcare provides rigorous coverage on several generations of techniques, including time;

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Condition Monitoring with Vibration Signals

Monitoring using Learning Algorithms; Classification Algorithms; and New Fault Diagnosis Frameworks designed for MCM. Readers will learn signal;

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EEG Brain Signal Classification for Epileptic Seizure Disorder Detection

learning techniques that have been modified and validated for the purpose of EEG signal classification using Discrete Wavelet Transform for the;

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Computational Learning Approaches to Data Analytics in Biomedical Applications

Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis;

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Biomedical Signal Processing for Healthcare Applications

modalities promotes better understanding, analysis, and application of biomedical signal processing for specific diseases. The major highlights;

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Behavior Analysis with Machine Learning Using R

Behavior Analysis with Machine Learning Using R introduces machine learning and deep learning concepts and algorithms applied to a diverse;

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EEG-Based Diagnosis of Alzheimer Disease

practical and easy-to-use guide for researchers in EEG signal processing techniques, Alzheimer's disease, and dementia diagnostics. The book;

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Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint

develops analysis techniques and measurement technologies for the quantitative characterization of materials, tissues and structures by non;

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Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint

develops analysis techniques and measurement technologies for the quantitative characterization of materials, tissues and structures by non;

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Biomedical Signal Analysis

The book will help assist a reader in the development of techniques for analysis of biomedical signals and computer aided diagnoses with a;

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Computational Intelligence in Biomedical Engineering

techniques commonly employed in the analysis of biomedical signals and in the improvement of signal to noise ratio. The text covers recent CI;

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Computational Intelligence in Biomedical Engineering

techniques commonly employed in the analysis of biomedical signals and in the improvement of signal to noise ratio. The text covers recent CI;

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Data Analytics in Biomedical Engineering and Healthcare

Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analytics, machine learning, and deep learning;

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TensorFlow Machine Learning Cookbook

Explore machine learning concepts using the latest numerical computing library - TensorFlow - with the help of this comprehensive cookbook;

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Building Machine Learning Pipelines Automating Model Life Cycles with Tensorflow

practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow;

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Practical Time Series Analysis Prediction with Statistics and Machine Learning

series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use;

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Statistical Learning for Biomedical Data

of probability and computer science but are not yet widely used in biomedical research. This introduction brings learning machine techniques to the;

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Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis

deep learning in clinical applicationsIntroduces several techniques for medical image processing and analysis for CAD systems design;

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Python Machine Learning -

Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries;

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Deep Learning for Biomedical Data Analysis

This book is the first overview on Deep Learning (DL) for biomedical data analysis. It surveys the most recent techniques and approaches;

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Introduction to Data Science

experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis;

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Machine Learning with Scala Quick Start Guide

covers tree-based ensemble techniques for solving both classification and regression problems. Moving ahead, it covers unsupervised learning;

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Mastering Java Machine Learning

tools in a wide range of techniques, with code and practical usage. * More than 10 real-world case studies in machine learning highlighting;

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