Lecturer: Prof. Woo Youn Kim, TA: Jaechang Lim
- AI has become a big social issue as it spreads rapidly to science, industry, and even daily life. Deep learning techniques has attracted great attention as a new powerful tool for chemical research. In this course, we will discuss the role of artificial intelligence in modern chemistry and look at the latest trends in this field. It aims to learn practical knowledge that can be used in actual research field through theory and practice focused on deep learning.
- This is the repository for materials of KAIST 2019 fall Artificial Intelligence and Chemistry.
- We use Google colab for all practices.
- Webiste: https://aceteamkaist.wixsite.com/home
Practice 02-06: Predicting molecular property, LogP in this practice, using various architectures of neural networks
Practice 07: Generating new SMILES string using variational autoencoder
- Practice 02: Linear regression
- Practice 03: Multilayer perceptron with non-linear activation
- Practice 04: Convolutional neural network
- Practice 05: Recurrent neural network
- Practice 06: Graph convolutional neural network
- Practice 07: Variational autoencoder