Welcome
The second edition of the “Cheminformatics, Automation and Machine Learning in Chemistry: from fundamental concepts to emerging techniques” (or CAMLC for short) workshop aims to introduce attendees to the use and development of emerging digital technologies in chemistry. Initially, attendees will review various functions of Python, particularly those related to modules commonly used in cheminformatics. Once users are familiar with Python environments and Jupyter Notebooks, machine learning and data science will be introduced, with a focus on state-of-the-art implementations in the field of chemistry. It is particularly relevant for attendees who work with the following:
- Homogeneous or finite systems
Note: the workshop is not recommended for researchers working on PBC-materials or MD-enzymes) - Machine learning modeling
- Database generation
- Gaussian and ORCA calculations
- Quantum mechanics and machine learning automated workflows
- Applications to catalyst design, mechanistic modeling, and drug discovery
