Machine Learning in Farm Animal Behavior using Python

Machine Learning in Farm Animal Behavior using Python

Natasa Kleanthous, Abir Hussain

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About this title

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 supervised, 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.

Details

Publisher
CRC Press
Language
EN
Format
EPUB
Published
ISBN
9781040328361
File protection
Watermark — opens on any reader, no extra account needed