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Test Data Engineering

This is the first technical book that considers tests as public tools and examines how to engineer and process test data, extract the;

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Software Testing Concepts & Operations

testing concepts, test data generation, test deployment analysis, and software test management This book examines the principles, concepts, and;

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Newnes Engineering Materials Pocket Book

This pocket book provides basic definitions, test methods and comprehensive data on the most commonly encountered engineering materials. A;

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Newnes Engineering Materials Pocket Book

This pocket book provides basic definitions, test methods and comprehensive data on the most commonly encountered engineering materials. A;

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Engineering Materials Pocket Book

This pocket book provides basic definitions, test methods and comprehensive data on the most commonly encountered engineering materials. A;

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Wide-Area Data Network Performance Engineering

A guide to wide-area data network performance engineering. It discusses the skills needed to design a router network carrying a variety;

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Introduction to Aerospace Engineering with a Flight Test Perspective

Comprehensive textbook which introduces the fundamentals of aerospace engineering with a flight test perspective Introduction to Aerospace;

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Composite Materials Handbook (CHM-17): Volume 2

historical data from previous versions of the handbook that do not meet current data sampling, test methodology, or documentation requirements, but;

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Testing in the digital age

roadmap split up in fi ve hops. With everything digital there are more possibilities for test automation and piles of (test) data growing out;

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Geotechnical Engineering Investigation Handbook

* Global positioning systems (GPS) * Geophysical exploration * Cone penetrometer testing * Earthquake studies * Digitizing of data;

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Equivalence and Noninferiority Tests for Quality, Manufacturing and Test Engineers

verification test data to demonstrate equivalence and noninferiority in engineering and applied science. The book covers numerous tests drawn;

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Equivalence and Noninferiority Tests for Quality, Manufacturing and Test Engineers

verification test data to demonstrate equivalence and noninferiority in engineering and applied science. The book covers numerous tests drawn;

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Dynamic Mechanical Analysis for Plastics Engineering

information. All of the information for 120 families of thermoplastics is based on independent test data conducted exclusively for this product and;

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Advances in Engineering Research

ground vibration test results and mass data.;

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Expert Trading Systems

useful results fast. Provides data modeling methodology used to develop trading systems. Shows how to design, test, and measure the;

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Statistical Inference for Engineers and Data Scientists

in engineering and data science, ideal for graduate students taking courses on statistical inference and detection and estimation, and an invaluable;

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Manual of Geotechnical Laboratory Soil Testing

Presents the step-by-step procedures for various tests based on relevant standards Interprets soil analytical data and illustrates empirical;

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Traffic Engineer II

The Traffic Engineer II Passbook® prepares you for your test by allowing you to take practice exams in the subjects you need to study. It;

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Handbook of Materials Selection for Engineering Applications

and manufacturing costs, drawing on such sources as vendor supplied and quality control test data.;

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Computational Intelligence Techniques and Their Applications to Software Engineering Problems

, defect prediction, maintainability and quality prediction, size estimation, vulnerability prediction, test case selection and prioritization, and;

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Theory and Design for Mechanical Measurements

interpreting test results. Coverage of topics, applications and devices has been updated including information on data acquisition hardware and;

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QUANTILE REGRESSION - Applications on Experimental and Cross Section Data Using EVIEWS

QUANTILE REGRESSION A thorough presentation of Quantile Regression designed to help readers obtain richer information from data analyses;

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Feature Engineering for Machine Learning and Data Analytics

Feature engineering plays a vital role in big data analytics. Machine learning and data mining algorithms cannot work without data. Little;

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