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Viser: Deep Learning for the Life Sciences - Applying Deep Learning to Genomics, Microscopy, Drug Discovery, and More
Deep Learning for the Life Sciences Vital Source e-bog
Bharath Ramsundar, Peter Eastman, Patrick Walters og Vijay Pande
(2019)
Deep Learning for the Life Sciences
Applying Deep Learning to Genomics, Microscopy, Drug Discovery, and More
Bharath Ramsundar, Peter Eastman, Pat Walters og Vijay Pande
(2019)
Sprog: Engelsk
om ca. 10 hverdage
Detaljer om varen
- 1. Udgave
- Vital Source searchable e-book (Reflowable pages)
- Udgiver: O'Reilly Media, Inc (April 2019)
- Forfattere: Bharath Ramsundar, Peter Eastman, Patrick Walters og Vijay Pande
- ISBN: 9781492039785
Bookshelf online: 5 år fra købsdato.
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Detaljer om varen
- 1. Udgave
- Paperback: 233 sider
- Udgiver: O'Reilly Media, Incorporated (Maj 2019)
- Forfattere: Bharath Ramsundar, Peter Eastman, Pat Walters og Vijay Pande
- ISBN: 9781492039839
Deep learning has already achieved remarkable results in many fields. Now it's making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields.
Ideal for practicing developers and scientists ready to apply their skills to scientific applications such as biology, genetics, and drug discovery, this book introduces several deep network primitives. You'll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicine--an example that represents one of science's greatest challenges.
- Learn the basics of performing machine learning on molecular data
- Understand why deep learning is a powerful tool for genetics and genomics
- Apply deep learning to understand biophysical systems
- Get a brief introduction to machine learning with DeepChem
- Use deep learning to analyze microscopic images
- Analyze medical scans using deep learning techniques
- Learn about variational autoencoders and generative adversarial networks
- Interpret what your model is doing and how it's working