Machine Learning in Farm Animal Behavior using Python (Original PDF from Publisher)

Description

As smart farming becomes central to agricultural innovation, the integration of machine learning (ML) in animal behavior analysis is transforming how we ensure animal welfare, detect diseases early, and optimize farm operations. Machine Learning in Farm Animal Behavior using Python (1st Edition, 2025) is the first comprehensive guide dedicated to applying machine learning techniques to real-world problems in farm animal behavior.

Written for a multidisciplinary audience, this book is tailored for animal scientists, machine learning practitioners, agricultural engineers, veterinarians, and graduate students interested in applying data-driven technologies to livestock systems. The text balances theory, code, and application—offering hands-on Python examples that can be adapted for both academic research and industrial practice.

Key Features & Highlights

• Hands-On Python Integration: Includes annotated Python code snippets for behavior modeling, detection, and prediction.
• Real-World Farm Applications: Focuses on behavior tracking, health monitoring, anomaly detection, and smart sensors.
• Interdisciplinary Approach: Merges concepts from animal science, machine learning, and IoT for robust solutions.
• Case Studies & Practical Use Cases: Learn from applied examples in dairy, poultry, swine, and other livestock sectors.
• Up-to-Date Content: Incorporates current ML algorithms and the latest tools used in precision agriculture.
• Original Publisher PDF: Full-color images, tables, and formatting preserved for optimal reading experience.

What You’ll Learn – Chapter Overview

This book includes core chapters on:

• Machine learning fundamentals for animal behavior analysis
• Data acquisition via sensors and video monitoring
• Behavioral pattern recognition and classification
• Anomaly detection for early health issue prediction
• Python-based implementation of ML models in livestock systems
• Ethical considerations in animal monitoring and data use

Whether you’re building a predictive model for lameness detection in cows or using deep learning to monitor poultry activity, this guide offers the foundational and applied knowledge you need.

About the Author

The author is a recognized expert at the intersection of precision livestock farming, computer science, and animal welfare. With academic and field research spanning both agriculture and AI, their work empowers the next generation of smart farming innovation.

Format & Technical Details

• Format: Original PDF (Publisher Version from CRC Press)
• File Size: Approx. 20–40MB depending on embedded images/code
• Language: English
• Device Compatibility: Compatible with PC, Mac, tablets, and any PDF-enabled e-readers

Frequently Asked Questions

Q: Do I need to be a machine learning expert to use this book?
A: No. The book is designed for readers with basic Python knowledge and provides step-by-step guidance on applying ML to animal behavior data.

Q: Can I use the included Python code for my own farm or research project?
A: Yes! The code examples are meant to be adaptable for real-world applications in both academic research and commercial farm settings.