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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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Multifrequency Electromagnetic Data Interpretation for Subsurface Characterization

Multifrequency Electromagnetic Data Interpretation for Subsurface Characterization focuses on the development and application;

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A Primer on Machine Learning in Subsurface Geosciences

-for-purpose machine learning models to solve real-world problems in subsurface geosciences.;

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Advances in Machine Learning Applications in Software Engineering

provides analysis, characterization, and refinement of software engineering data in terms of machine learning methods. This book depicts;

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Groundwater Engineering: A Technical Approach to Hydrogeology, Contaminant Transport and Groundwater Remediation

an ideal learning resource for upper-undergraduate and graduate students of civil engineering, environmental engineering, and geology, as;

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Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint

features for machine learning and pattern classification in time-domain signals. Whether for medical imaging or structural health monitoring, it;

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Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint

features for machine learning and pattern classification in time-domain signals. Whether for medical imaging or structural health monitoring, it;

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Seeing into the Earth

volume makes recommendations for linking characterization and cost savings, closing the gap between the state of science and the state of the;

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Subsurface Contamination Monitoring Using Laser Fluorescence

development, testing, and performance of a new laser-induced fluorescence soil probe. A screening tool for site characterization, this probe has the;

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Active Seismic Tomography

earth's subsurface. Active Seismic Tomography: Theory and Applications describes current technologies for the study of seismic velocities and the;

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Subsurface Hydrology

> Approaches to hydrologie data integration Data integration for characterization of hydrologie properties Data;

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Seismic Reservoir Modeling - Theory, Examples, and Algorithms

Seismic reservoir characterization aims to build 3-dimensional models of rock and fluid properties, including elastic and petrophysical;

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Optical Phenomenology and Applications

This book is an introduction to techniques and applications of optical methods for materials Characterization in civil and environmental;

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Machine Learning Applications Using Python

Gain practical skills in machine learning for finance, healthcare, and retail. This book uses a hands-on approach by providing case studies;

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Machine Learning for Oracle Database Professionals

mechanisms for process and deployment. Seasoned database professionals looking to make the leap into machine learning as a growth path will find much;

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Geostatistical Methods for Reservoir Geophysics

valuable resource for students who are interested in learning more about the fascinating world of geostatistics and reservoir modeling and;

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Machine Learning for Finance

A guide to advances in machine learning for financial professionals, with working Python code Key Features Explore advances in machine;

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Machine Learning in Industry

learning. It points out the difference between the techniques and their suitability for specific applications. This book also describes different;

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Machine Learning Foundations

the fundamental materials, background, and simple machine learning algorithms, as the preparation for studying machine learning algorithms;

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Beginning Machine Learning in iOS

. Many applications on iPhone use machine learning: Siri to serve voice-based requests, the Photos app for facial recognition, and Facebook to;

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Human-in-the-Loop Machine Learning

. Human-in-the-Loop Machine Learning is a practical guide to optimizing the entire machine learning process, including techniques for annotation;

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Python Machine Learning

Python makes machine learning easy for beginners and experienced developers With computing power increasing exponentially and costs;

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Machine Learning with scikit-learn Quick Start Guide

DescriptionScikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning;

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Remediation Engineering of Contaminated Soils

design and methodology, characterization of geomedia, monitoring of contaminants in the subsurface, and waste containment. Cites specific case;

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AWS Certified Machine Learning Specialty: MLS-C01 Certification Guide

and deploy machine learning models to the Amazon Web Services (AWS) cloud Learn all about the AWS services available for machine learning;

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Reinforcement and Systemic Machine Learning for Decision Making

Reinforcement and Systemic Machine Learning for Decision Making explores a newer and growing avenue of machine learning algorithm in the;

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Exam Ref 70-774 Perform Cloud Data Science with Azure Machine Learning

Learning services. Designed for experienced IT professionals ready to advance their status, Exam Ref focuses on the critical thinking and decision;

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