Shulph Ink
A Guide to Applied Machine Learning for Biologists
A Guide to Applied Machine Learning for Biologists
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This textbook provides an introductory guide to applied machine learning for biology students,familiarizing them with computer science and mathematics and their real-world applications in bioinformatics,systems biology,biological data analysis,and healthcare diagnosis and treatment.
Format: Hardback
Length: 262 pages
Publication date: 11 June 2023
Publisher: Springer International Publishing AG
This comprehensive textbook serves as an introductory guide to applied machine learning, particularly tailored for biology students. It aims to familiarize biology students with the fundamental principles of modern computer science and mathematics, while emphasizing their real-world applications. The book encompasses a comprehensive overview of computer systems and programming languages, providing a solid foundation for understanding the core concepts within computer systems. Readers are introduced to the realm of machine learning and artificial intelligence, specifically in the context of bioinformatics, where these applications are interconnected with systems biology, biological data analysis, predictions, and healthcare diagnosis and treatment.
The textbook offers a valuable resource for those seeking to delve into the field of computer-based technologies in biology. It employs a rich blend of case studies, real-world scenarios, and diverse examples to facilitate the reader's journey from the basic prerequisites to machine learning and its diverse applications. By presenting a holistic approach, the book equips students with the necessary skills and knowledge to leverage advanced computer-based technologies in their biology studies and future professional endeavors.
In summary, this textbook serves as an essential guide for biology students seeking to embrace the world of applied machine learning. It provides a solid foundation in computer science and mathematics, while delving into the realm of bioinformatics and its applications. With its comprehensive coverage, real-world examples, and practical insights, the book empowers students to excel in their computer-based biology studies and contribute to the field's advancements.
Weight: 582g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031222054
Edition number: 1st ed. 2023
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