Deep Learning for Biology: Harness AI to Solve Real-World Biology Problems - Softcover

Ravarani, Charles; Latysheva, Natasha

 
9781098168032: Deep Learning for Biology: Harness AI to Solve Real-World Biology Problems
Softcover
ISBN 10: 1098168038 ISBN 13: 9781098168032
Verlag: O'Reilly Media, 2025

Inhaltsangabe

Bridge the gap between modern machine learning and real-world biology with this practical, project-driven guide. Whether your background is in biology, software engineering, or data science, Deep Learning for Biology gives you the tools to develop deep learning models for tackling a wide range of biological problems.

Authors Charles Ravarani and Natasha Latysheva guide you through hands-on projects applying deep learning to domains like DNA, proteins, biological networks, medical images, and microscopy. Each chapter is a self-contained mini-project, with step-by-step explanations that teach you how to train and interpret deep learning models using real biological data.

  • Build models for real-world biological problems such as gene regulation, protein function prediction, drug interactions, and cancer detection
  • Apply architectures like convolutional neural networks, transformers, graph neural networks, and autoencoders
  • Use Python and interactive notebooks for hands-on learning
  • Build problem-solving intuition that generalizes beyond biology

Whether you're exploring new methods, transitioning into computational biology, or looking to make sense of machine learning in your field, this book offers a clear and approachable path forward.

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Über die Autorin bzw. den Autor

Charles Ravarani is a biologist and software engineer who is currently Chief Technology Officer at biotx.ai, a computational drug discovery startup. He completed his PhD and post-doc in computational biology at the University of Cambridge, and in addition to his outstanding academic contributions, Charles is a software development veteran, has consulted various organizations, and has a passion for teaching programming and machine learning topics.

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Verlag
O'Reilly Media
Erscheinungsdatum
2025
Sprache
Englisch
ISBN 10 
1098168038
ISBN 13 
9781098168032
Einband
Taschenbuch
Anzahl der Seiten
434
Kontakt zum Hersteller
O'Reilly
https://oreilly.com

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