CH485---Artificial-Intelligence-and-Chemistry

Lecturer : Woo Youn Kim, TA : Seongok Ryu, 2018 Fall

Deparment of Chemistry, Korea Advanced Institute of Science and Technology (KAIST)

In this course, CH485 - Artificial Intelligence and Chemistry, we will learn applications of machine learning for chemistry. After successfully finishing this course, students would be confident in understanding and implementing AI models for chemical/molecular applications.

This repository is managed by Seongok Ryu, and lecture notes/example codes about contents will be uploaded. (190228) Seongok Ryu updated lecture notes, practice notes that utilized in the lectures.

Lectures in this course

• Lecture 01 : Introduction
• Lecture 02 : Math review
• Lecture 03 : Regression and Classification
• Lecture 04 : Support Vector Machine
• Lecture 05 : Multi Layer Perceptron, part1
• Lecture 06 : Multi Layer Perceptron, part2 - regularization
• Lecture 07 : Convolutional Neural Network (CNN)
• Lecture 08 : Molecular graph and Graph Neural Network (GNN)
• Lecture 09 : SMILES and Recurrent Neural Network (RNN)
• Lecture 10 : Graph Neural Network and Message Passing Neural Network (MPNN)
• Lecture 11 : Variational Autoencoder (VAE)
• Lecture 12 : Reinforcement Learning (RL)

Practices in this course

• Practice 01 : Introduction
• Practice 02 : RDKit and SVM
• Practice 03 : MLP and tensorflow
• Practice 04 : MLP and regularization
• Practice 05 : SMILES and CNN
• Practice 06 : Molecular graph and GNN
• Practice 07 : SMILES and RNN
• Practice 08 : Overview on molecular property predictions
• Practice 09 : Molecular generative model -1-
• Practice 10 : Molecular generative model -2-

Fruitful materials

• Over 200 of the Best Machine Learning, NLP, and Python Tutorials — 2018 Edition, https://medium.com/machine-learning-in-practice/over-200-of-the-best-machine-learning-nlp-and-python-tutorials-2018-edition-dd8cf53cb7dc
• Online deep learning textbook written by Goodfellow, Bengio, and Couville, https://www.deeplearningbook.org/
• Reinforcement Learning lecture, by David Silver, http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html
• Legendary lectures of 'Linear algebra' and 'Probabilistics', https://www.youtube.com/watch?v=ZK3O402wf1c&list=PLE7DDD91010BC51F8&index=1, https://www.youtube.com/watch?v=KbB0FjPg0mw&list=PL2SOU6wwxB0uwwH80KTQ6ht66KWxbzTIo&index=1