Machine Learning For Labeling – alle Bücher, Seite 2 online kaufen

Qiang Huang
Domain-informed Machine Learning for Smart Manufacturing

This book introduces the state-of-the-art understanding on domain-informed machine learning (DIML) for advanced manufacturing. Methods and case studies presented in this volume show how complicated engine…

lieferbar in mind. 4 Wochen

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Denisse L. Argote, Pedro A. López-García, Manuel A. Torres-García
Machine Learning for Archaeological Applications in R

This Element highlights the employment within archaeology of classification methods developed in the field of chemometrics, artificial intelligence, and Bayesian statistics. It also provides a detailed ex…

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Statistical Machine Learning for Engineering with Applications

This book offers a leisurely introduction to the concepts and methods of machine learning. Readers will learn about classification trees, Bayesian learning, neural networks and deep learning, the design o…

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Denisse L. Argote, Pedro A. López-García, Manuel A. Torres-García
Machine Learning for Archaeological Applications in R

This Element highlights the employment within archaeology of classification methods developed in the field of chemometrics, artificial intelligence, and Bayesian statistics. It also provides a detailed ex…

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Machine Learning for Indoor Localization and Navigation

While GPS is the de-facto solution for outdoor positioning with a clear sky view, there is no prevailing technology for GPS-deprived areas, including dense city centers, urban canyons, buildings and other…

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Machine Learning for Econometrics and Related Topics

In the last decades, machine learning techniques ¿ especially techniques of deep learning ¿ led to numerous successes in many application areas, including economics. The use of machine learning in economi…

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Machine Learning and Data Mining for Sports Analytics

This book constitutes the refereed proceedings of the 11th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2024, held in Vilnius, Lithuania, on September 9, 2024.The …

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Computational Intelligence for Machine Learning and Healthcare Informatics

This book presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It is intended to provide a uniqu…

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A Guide to Applied Machine Learning for Biologists

This textbook is an introductory guide to applied machine learning, specifically for biology students. It familiarizes biology students with the basics of modern computer science and mathematics and empha…

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Explainable Machine Learning for Multimedia Based Healthcare Applications

This book covers the latest research studies regarding Explainable Machine Learning used in multimedia-based healthcare applications. In this context, the content includes not only introductions for appli…

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Mahima
Limitations of Traditional Training Methods for Crowd Workers in Machine Classification and Labeling Tasks

Another type of broadly-used method is training the crowd workers before assigning them to a given MCS task [69, 78]. This type of methods overcome the problem of embedding gold instances in the whole ann…

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Prashad
Optimization Algorithms for Machine Learning: Theory and Practice

In the realm of machine learning, optimization algorithms play a pivotal role in refining models for optimal performance. These algorithms, ranging from classic gradient descent to advanced techniques lik…

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Tsutomu Sasao
Classification Functions for Machine Learning and Data Mining

This book introduces a novel perspective on machine learning, offering distinct advantages over neural network-based techniques. This approach boasts a reduced hardware requirement, lower power consumptio…

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Machine Learning Methods for Multi-Omics Data Integration

The advancement of biomedical engineering has enabled the generation of multi-omics data by developing high-throughput technologies, such as next-generation sequencing, mass spectrometry, and microarrays.…

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Machine Learning for Powder-Based Metal Additive Manufacturing

Machine Learning for Powder-based Metal Additive Manufacturing outlines machine learning (ML) methods for additive manufacturing (AM) of metals that will improve product quality, optimize manufacturing pr…

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Practical Machine Learning Tools and Techniques for Industrial Applications

The main goal of the book is to provide a comprehensive and accessible guide that empowers readers to understand, apply, and leverage machine learning algorithms and techniques effectively in real-world s…

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Artificial Intelligence and Machine Learning for Industry 4.0

Intelligent automation is widely considered to have the greatest potential for Industry 4.0 innovations for corporations. Industrial machinery is increasingly being upgraded to intelligent machines that c…

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Anupam Bagchi, Pramod Gupta
Essentials of Python for Artificial Intelligence and Machine Learning

This book introduces the essentials of Python for the emerging fields of Machine Learning (ML) and Artificial Intelligence (AI). The authors explore the use of Python's advanced module features and apply …

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Ali Othman Albaji
Machine Learning for Environmental Noise Classification in Smart Cities

We present a Machine Learning (ML) approach to monitoring and classifying noise pollution. Both methods of monitoring and classification have been proven successful. MATLAB and Python code was generated t…

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Machine Learning for Cyber Physical System: Advances and Challenges

This book provides a comprehensive platform for learning the state-of-the-art machine learning algorithms for solving several cybersecurity issues. It is helpful in guiding for the implementation of smart…

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