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Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces

Pascal Laube presents machine learning approaches for three key problems of reverse engineering of defective structured surfaces;

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Product Design

engineering and teardowns offer a new better paradigm for design instruction, permitting a modern learning cycle of experience, hypothesis;

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Advances in Machine Learning Applications in Software Engineering

establish predictive models for software quality. Advances in Machine Learning Applications in Software Engineering offers readers direction for;

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Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 2

Alternating Diffusion: A Geometric Approach for Sensor Fusion, Generating Structured TV-based Priors and Associated Primal-dual Methods, Graph-based;

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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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Functional Reverse Engineering of Strategic and Non-Strategic Machine Tools

for capacity building in academia, covering how to promote enterprises of functional reverse engineering enterprises. It also discusses;

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Reverse Engineering

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to;

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Classification of Malware

unknown complex malware. In this work, a new approach to detect malware, which uses reverse engineering and machine learning techniques;

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Empowering Artificial Intelligence Through Machine Learning

. Topics include techniques and methods in artificial intelligence for making machines intelligent, machine learning in healthcare, using machine;

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Machine Learning Pocket Reference Working with Structured Data in Python

learning process and walks you through classification with structured data. You'll also learn methods for clustering, predicting a continuous value;

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Machine Learning

majors. It is also a useful reference resource for researchers and practitioners of machine learning.;

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Machine Learning and Knowledge Discovery for Engineering Systems Health Management

Machine Learning and Knowledge Discovery for Engineering Systems Health Management presents state-of-the-art tools and techniques for;

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Data-Driven Science and Engineering

trains mathematical scientists and engineers for the next generation of scientific discovery by offering a broad overview of the growing;

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Practical Machine Learning with Python

examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science;

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Kernels For Structured Data

applied to structured data. Kernel methods are a class of state-of-the-art learning algorithms that exhibit excellent learning results in several;

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Advanced Research in Applied Artificial Intelligence

cognitive computing and intelligent interaction; spatio-temporal datamining, structured learning and their applications; decision making and;

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Machine Learning Engineering with Python

with building and deploying robust machine learning solutions. As you advance, you'll explore how to create your own toolsets for training and;

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Thermal Engineering Research Developments

optimisation process for a reverse cycle machine, and numerical results concerning the simulation of semiconductors melts with free capillary surfaces.;

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Feature Engineering for Machine Learning and Data Analytics

depends on the quality of the available features. Feature Engineering for Machine Learning and Data Analytics provides a comprehensive;

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Feature Engineering for Machine Learning and Data Analytics

depends on the quality of the available features. Feature Engineering for Machine Learning and Data Analytics provides a comprehensive;

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Metric Learning

thorough review of the metric learning literature that covers algorithms, theory and applications for both numerical and structured data. We first;

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Machine Learning in Bioinformatics

Learning in Bioinformatics is an indispensable resource for computer scientists, engineers, biologists, mathematicians, researchers, clinicians;

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Statistical and Machine Learning Approaches for Network Analysis

weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross;

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Proceedings of International Conference on Big Data Machine Learning and their

This book contains high-quality peer-reviewed papers of the International Conference on Big Data, Machine Learning and their Applications;

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Machine Learning and Systems Engineering

reference text for researchers and graduate students, working on machine learning and systems engineering.;

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Reverse Engineering

This edited collection of essays from world-leading academic and industrial authors yields insight i;...

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