This course is an introduction to machine learning applied to chemistry. You will learn machine learning fundamentals, from basic linear regression to deep learning with neural networks. Machine learning is a very broad topic, and this course will not be an exhaustive review of all existing methods. Instead, specific focus will be given on how, in practice, to set up machine learning models using Python. This will be illustrated on concrete examples in chemistry. The course consists in four lectures organized as follows:
1) Introduction: machine learning fundamentals
2) Machine learning for chemistry: hands-on training on concrete examples
3) Deep learning for chemistry
4) And now, play on! mini-project
- 教師: Rolland Nicolas