9781032628714 - machine learning in farm animal behavior using python di kleanthous, natasa; hussain, abir (10 risultati)

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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Paperback. Condizione: Brand New. 394 pages. 6.14x0.93x9.21 inches. In Stock.

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Da: moluna, Greven, Germaniamoluna
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Condizione: New. Natasa Kleanthous holds a BSc in Management and Information Systems from the University of Nicosia, and an MSc in Computing and Information Systems from Liverpool John Moores University, UK. She earned her PhD from Liverpool John Moores .

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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. Neuware - This book is a comprehensive guide to applying machine learning to animal behavior analysis, focusing on activity recognition in farm animals. It begins by introducing key concepts of animal behavior and ethology, followed by an exploration of machine learning techniques, including supervi…sed, unsupervised, semi-supervised, and reinforcement learning. The practical section covers essential steps like data collection, preprocessing, exploratory data analysis, feature extraction, model training, and evaluation, using Python.The book emphasizes the importance of high-quality data and discusses various sensors and annotation methods for effective data collection. It addresses key machine learning challenges such as generalization and data issues. Advanced topics include feature selection, model selection, hyperparameter tuning, and deep learning algorithms. Practical examples and Python implementations are provided throughout, offering hands-on experience for researchers, students, and professionals aiming to apply machine learning to animal behavior analysis.

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Paperback. Condizione: new. Paperback. This book is a comprehensive guide to applying machine learning to animal behavior analysis, focusing on activity recognition in farm animals. It begins by introducing key concepts of animal behavior and ethology, followed by an exploration of machine learning techniques, including supervis…ed, unsupervised, semi-supervised, and reinforcement learning. The practical section covers essential steps like data collection, preprocessing, exploratory data analysis, feature extraction, model training, and evaluation, using Python.The book emphasizes the importance of high-quality data and discusses various sensors and annotation methods for effective data collection. It addresses key machine learning challenges such as generalization and data issues. Advanced topics include feature selection, model selection, hyperparameter tuning, and deep learning algorithms. Practical examples and Python implementations are provided throughout, offering hands-on experience for researchers, students, and professionals aiming to apply machine learning to animal behavior analysis. The book includes detailed Python examples for each phase, making it an essential resource for researchers and practitioners in animal behavior and technology. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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Paperback. Condizione: new. Paperback. This book is a comprehensive guide to applying machine learning to animal behavior analysis, focusing on activity recognition in farm animals. It begins by introducing key concepts of animal behavior and ethology, followed by an exploration of machine learning techniques, including supervis…ed, unsupervised, semi-supervised, and reinforcement learning. The practical section covers essential steps like data collection, preprocessing, exploratory data analysis, feature extraction, model training, and evaluation, using Python.The book emphasizes the importance of high-quality data and discusses various sensors and annotation methods for effective data collection. It addresses key machine learning challenges such as generalization and data issues. Advanced topics include feature selection, model selection, hyperparameter tuning, and deep learning algorithms. Practical examples and Python implementations are provided throughout, offering hands-on experience for researchers, students, and professionals aiming to apply machine learning to animal behavior analysis. The book includes detailed Python examples for each phase, making it an essential resource for researchers and practitioners in animal behavior and technology. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
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Paperback. Condizione: new. Paperback. This book is a comprehensive guide to applying machine learning to animal behavior analysis, focusing on activity recognition in farm animals. It begins by introducing key concepts of animal behavior and ethology, followed by an exploration of machine learning techniques, including supervis…ed, unsupervised, semi-supervised, and reinforcement learning. The practical section covers essential steps like data collection, preprocessing, exploratory data analysis, feature extraction, model training, and evaluation, using Python.The book emphasizes the importance of high-quality data and discusses various sensors and annotation methods for effective data collection. It addresses key machine learning challenges such as generalization and data issues. Advanced topics include feature selection, model selection, hyperparameter tuning, and deep learning algorithms. Practical examples and Python implementations are provided throughout, offering hands-on experience for researchers, students, and professionals aiming to apply machine learning to animal behavior analysis. The book includes detailed Python examples for each phase, making it an essential resource for researchers and practitioners in animal behavior and technology. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.