Deep Learning for Biology

Harness AI to Solve Real-World Biology Problems

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Beschreibung

<p>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, <em>Deep Learning for Biology</em> gives you the tools to develop deep learning models for tackling a wide range of biological problems.</p> <p>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.</p> <ul> <li>Build models for real-world biological problems such as gene regulation, protein function prediction, drug interactions, and cancer detection</li> <li>Apply architectures like convolutional neural networks, transformers, graph neural networks, and autoencoders</li> <li>Use Python and interactive notebooks for hands-on learning</li> <li>Build problem-solving intuition that generalizes beyond biology</li> </ul> <p>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.</p>

Artikeldetails

EAN

9781098168032

Sprache

Englisch

Einband / Art

Taschenbuch

Maße

232 x 174 x 23 mm

Erscheinungsjahr

2025

Verlag / Hersteller

O'Reilly Media