Deep Learning for Biology: Harness AI to Solve Real-World Biology Problems by Charles Ravarani, Natasha Latysheva
English | August 26th, 2025 | ISBN: 1098168038 | 434 pages | True EPUB (Retail Copy) | 14.90 MB
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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