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Modeling Machine Learning and Astronomy

This book constitutes the proceedings of the First International Conference on Modeling, Machine Learning and Astronomy, MMLA 2019, held;

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Machine Learning Modeling for IoUT Networks

This book discusses how machine learning and the Internet of Things (IoT) are playing a part in smart control of underwater environments;

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Machine Learning for Time Series Forecasting with Python

machine learning scientist and economist, corrects that deficiency by providing readers with comprehensive and approachable explanation and;

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A Primer on Machine Learning Applications in Civil Engineering

Machine learning has undergone rapid growth in diversification and practicality, and the repertoire of techniques has evolved and expanded;

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Introduction to Statistical Machine Learning

, medicine, astronomy, physics, and materials. Introduction to Statistical Machine Learning provides a general introduction to machine;

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Machine Learning, Low-Rank Approximations and Reduced Order Modeling in Computational Mechanics

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Machine Learning for Vision-Based Motion Analysis: Theory and Techniques

application of statistical machine learning algorithms for object tracking, activity modeling, and recognition. Developed from expert contributions;

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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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The Essentials of Machine Learning in Finance and Accounting

assets and markets and correlates them with enterprises' profitability * Introduces advanced and novel machine learning techniques in finance;

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The Essentials of Machine Learning in Finance and Accounting

assets and markets and correlates them with enterprises' profitability * Introduces advanced and novel machine learning techniques in finance;

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Machine Learning and Big Data Analytics Paradigms

This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered;

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Machine Learning and Metaheuristics Algorithms, and Applications

This book constitutes the refereed proceedings of the First Symposium on Machine Learning and Metaheuristics Algorithms, and Applications;

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Machine Learning in Finance

This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and;

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Machine Learning in Finance

This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and;

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Computational Trust Models and Machine Learning

Computational Trust Models and Machine Learning provides a detailed introduction to the concept of trust and its application in various;

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Context-Aware Machine Learning and Mobile Data Analytics

context-aware intelligent applications and services. The presented machine learning-based techniques can be employed in a wide range of real-world;

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Machine Learning and Systems Engineering

A large international conference on Advances in Machine Learning and Systems Engineering was held in UC Berkeley, California, USA, October;

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Applied Supervised Learning with Python

learning toolkit-from performing basic data cleaning and processing to working with a range of regression and classification algorithms. Once;

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Machine Learning in Radiation Oncology

This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory;

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Intelligent Learning Systems

Intelligent (machine) learning is a subfield of artificial intelligence and it originates from the researches in the pattern recognition;

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Time Series Algorithms Recipes

. You'll also gain insight into classic machine learning-based regression models like randomForest, Xgboost, and LightGBM for forecasting problems;

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Machine Learning Using R

shows you how to work with a machine-learning algorithm and use it to build a ML model from raw data. You will see how to use R programming with;

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Probabilistic Machine Learning

A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian;

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Machine Learning and Metaheuristics Algorithms and Applications

This book constitutes the refereed proceedings of the Second Symposium on Machine Learning and Metaheuristics Algorithms, and Applications;

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Graph-Powered Machine Learning

At its core, machine learning is about efficiently identifying patterns and relationships in data. Many tasks, such as finding associations;

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Evolutionary Computation Machine Learning and Data Mining in Bioinformatics

This book constitutes the refereed proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining;

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