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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-

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