DeepChem aims to provide a high-quality open-source toolchain that democratizes the use of deep learning in drug discovery, materials science, quantum chemistry, and biology. DeepChem currently supports Python 3.7 through 3.9 and requires these packages on any condition. DeepChem has a number of "soft" requirements. If you face some errors like ImportError: This class requires XXXX, you may need to install some packages. Deepchem provides support for TensorFlow, PyTorch, JAX and each requires an individual pip Installation. The DeepChem project maintains an extensive collection of tutorials. All tutorials are designed to be run on Google collab (or locally if you prefer). Tutorials are arranged in a suggested learning sequence that will take you from beginner to proficient at molecular machine learning and computational biology more broadly.
Features
- The DeepChem project works to democratize deep learning for science
- Deepchem provides support for tensorflow, pytorch, jax and each require a individual pip Installation
- DeepChem is managed by a team of open source contributors
- The DeepChem project maintains an extensive collection of tutorials
- DeepChem stable version can be installed using pip or conda
- Supports Python 3.7 through 3.9
Project Samples
