£108.78

Springer Machine Learning and Deep Learning in Toxicology Book

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Description

Explore the intersection of advanced computing and safety science with this comprehensive volume from Springer. This book provides a detailed collection of machine learning and deep learning algorithms, architectures, and software tools specifically designed for predictive toxicology. Readers will find a compilation of recent applications that utilize state-of-the-art techniques to analyze various toxicological endpoint data. By combining informative text with helpful figures and tables, the content explains how these modern computational methods are applied in real-world scenarios. This resource is essential for those looking to understand the current landscape of predictive toxicology through the lens of advanced machine learning and deep learning methodologies.

Key Features

Comprehensive collection of machine learning and deep learning algorithms and architectures for toxicological research.

Detailed overview of software tools developed and widely applied in the field of predictive toxicology.

Analysis of recent applications using state-of-the-art deep learning techniques on various toxicological endpoint data.

Informative presentation featuring text, figures, and tables to summarize complex computational methods.

Focused content on the practical application of machine learning methods within the sciences.

Product Specifications

Format
Hardcover
Domain
Amazon UK
Release Date
08 February 2023
Listed Since
29 September 2022

Barcode

No barcode data available

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