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Springer Machine Learning Methods for Ecological Applications - Springer

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Description

Machine Learning Methods for Ecological Applications is the first comprehensive text designed specifically for professional ecologists seeking to apply machine learning to ecological research and problem-solving. Written primarily by practising ecologists and biologists, this Springer publication bridges the gap between computational methods and real-world ecological applications, with each chapter exploring how particular machine learning techniques address specific ecological challenges. The book provides practical guidance from experts who understand both the theoretical foundations of machine learning and the nuanced demands of ecological fieldwork and analysis. Whether you are investigating species distribution patterns, analysing biodiversity data, predicting ecosystem responses, or managing environmental monitoring programmes, this resource offers accessible entry points to machine learning methodologies tailored for ecological contexts. Recognised as an excellent starting point for ecologists new to machine learning, the book combines technical depth with ecological relevance, making advanced computational methods approachable for researchers without extensive programming backgrounds.

Key Features

Machine Learning Methods for Ecological Applications provides chapters written by ecologists and biologists who apply specific computational techniques to real ecological problems and datasets.

Springer's publication serves as the first dedicated text introducing machine learning methods to professional ecologists and environmental researchers.

Each chapter focuses on applying particular machine learning approaches to specific classes of ecological problems, from species modelling to ecosystem prediction.

The book offers an excellent starting point for ecologists transitioning from traditional statistical methods to machine learning-based analysis and research.

Written by practising experts in both ecology and computational science, the text balances technical accuracy with ecological relevance and practical applicability.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
29 October 2012
Listed Since
03 March 2013

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No barcode data available

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