Deep learning has already achieved remarkable results in many fields. Now itโs 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. Youโll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicineโan example that represents one of scienceโs greatest challenges.
โข Learn the basics of performing machine learning on molecular data
โข Understand why deep learning is a powerful tool for genetics and genomics
โข Apply deep learning to understand biophysical systems
โข Get a brief introduction to machine learning with DeepChem
โข Use deep learning to analyze microscopic images
โข Analyze medical scans using deep learning techniques
โข Learn about variational autoencoders and generative adversarial networks
โข Interpret what your model is doing and how itโs working