Deep Learning for Biology by Charles Ravarani
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.
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. Natasha Latysheva is a biologist and machine learning practitioner who is currently a Senior Research Engineer at Google DeepMind, specializing in deep learning for genomics. With a PhD in computational biology from the University of Cambridge and experience across several machine learning domains, her expertise is in bridging the gap between biology and machine learning. She is passionate about machine learning education and making complex technical topics accessible and exciting.
| SKU | Unavailable |
| ISBN 13 | 9781098168032 |
| ISBN 10 | 1098168038 |
| Title | Deep Learning for Biology |
| Author | Charles Ravarani |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | O'Reilly Media |
| Year published | 2025-09-02 |
| Number of pages | 300 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |