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A Guide to Applied Machine Learning for Biologists

Title
A Guide to Applied Machine Learning for Biologists [electronic resource] / edited by Mohammad "Sufian" Badar.
ISBN
9783031222061
Edition
1st ed. 2023.
Publication
Cham : Springer International Publishing : Imprint: Springer, 2023.
Physical Description
XIV, 262 p. 65 illus., 61 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
This textbook is an introductory guide to applied machine learning, specifically for biology students. It familiarizes biology students with the basics of modern computer science and mathematics and emphasizes the real-world applications of these subjects. The chapters give an overview of computer systems and programming languages to establish a basic understanding of the important concepts in computer systems. Readers are introduced to machine learning and artificial intelligence in the field of bioinformatics, connecting these applications to systems biology, biological data analysis and predictions, and healthcare diagnosis and treatment. This book offers a necessary foundation for more advanced computer-based technologies used in biology, employing case studies, real-world issues, and various examples to guide the reader from the basic prerequisites to machine learning and its applications.
Variant and related titles
Springer ENIN.
Other formats
Printed edition:
Printed edition:
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
June 23, 2023
Contents
Basics of Modern Computer Systems (Unix/Linux Centric)
The Python Programming Language ( A tool to enter the world of Machine Learning)
Basic Math
Introduction to the World of Bioinformatics
Introduction to Artificial Intelligence & ML
Fundamentals of ML
Applications in the field of Bioinformatics
Case Studies and a Minor Project
Future Prospects
Further Readings.
Also listed under
Badar, Mohammad "Sufian". editor.
SpringerLink (Online service)
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