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Developing VO2max Prediction Models Using Machine Learning Methods

The purpose of this work is to develop VO2max prediction models by using non-exercise, submaximal and hybrid variables by using Support;

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Hands-On Ensemble Learning with R

popular R packages. You will learn how to combine model predictions using different machine learning algorithms to build ensemble models;

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R Deep Learning Essentials

Build automatic classification and prediction models using unsupervised learning About This Book * Harness the ability to build;

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Machine Learning for Economics and Finance in TensorFlow 2

is concentrated on the identification of causal relationships in parsimonious statistical models; whereas machine learning is oriented towards prediction;

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Optimization in Machine Learning and Applications

further helps improve prediction and decision-making. The book also presents formulations of real-world machine learning problems, and discusses;

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Optimization in Machine Learning and Applications

further helps improve prediction and decision-making. The book also presents formulations of real-world machine learning problems, and discusses;

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Ensemble Machine Learning Cookbook

Implement machine learning algorithms to build ensemble models using Keras, H2O, Scikit-Learn, Pandas and more Key Features Apply popular;

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Supervised Machine Learning for Text Analysis in R

workflows for predictive modeling using text as features Compare traditional machine learning methods and deep learning methods for text data;

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Supervised Machine Learning for Text Analysis in R

workflows for predictive modeling using text as features Compare traditional machine learning methods and deep learning methods for text data;

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Data Analytics in Bioinformatics

Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine;

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Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering

optimum values and solutions for models such as artificial intelligence and machine learning. Research is a necessity for determining how these;

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Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering

optimum values and solutions for models such as artificial intelligence and machine learning. Research is a necessity for determining how these;

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Rank-Based Methods for Shrinkage and Selection

Shrinkage and Selection: With Application to Machine Learning describes techniques to produce higher quality data analysis in shrinkage and subset;

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Prediction Of Diabetes Blood Sugar Levels Using Machine Learning

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Advances in Machine Learning Applications in Software Engineering

Machine learning is the study of building computer programs that improve their performance through experience. To meet the challenge;

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Natural Language Processing

learning and deep learning models, text classification and structured prediction models, generative and discriminative models, supervised and;

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Machine Learning Approaches for Urban Computing

This book discusses various machine learning applications and models, developed using heterogeneous data, which helps in a comprehensive;

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Laser Scanning Systems in Highway and Safety Assessment: Analysis of Highway Geometry and Safety Using Lidar

This book aims to promote the core understanding of a proper modelling of road traffic accidents by deep learning methods using traffic;

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Analysis on Prediction of Swine Flu Using Machine Learning Algorithms

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Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction

Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction provides an up-to- date overview on the broad area of wind;

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Soft Computing

with asymmetrical triangular fuzzy numbers (TrFNs). Chapter Two examines the determination of stability number of layered slope using Adaptive;

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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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Intelligent Learning Systems

learning machine in fault classification of power transformer, prediction of solar irradiation using quantum support vector machine learning;

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Machine Learning Applications for Accounting Disclosure and Fraud Detection

is provided towards the prediction of the actual financial performance of the business activity. Machine Learning Applications for Accounting;

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Machine Learning in Bioinformatics

An introduction to machine learning methods and their applications to problems in bioinformatics Machine learning techniques are;

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Mastering Azure Machine Learning

Master expert techniques for building automated and highly scalable end-to-end machine learning models and pipelines in Azure using;

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Machine Learning Methods in the Environmental Sciences

Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This;

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