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Tue 14 Jan, Thu 16 Jan, ... Tue 4 Feb 2020
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Provided by: Department of Chemistry


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Chemistry: Machine Learning in Chemistry 101
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Tue 14 Jan, Thu 16 Jan, ... Tue 4 Feb 2020

Description

This graduate-level course gives an overview of machine learning (ML) techniques that are useful for solving problems in Chemistry, and particularly for the computational understanding and predictions of materials and molecules at the atomic level.

In the first part of the course, after taking a quick refresher of the basic concepts in probabilities and statistics, students will learn about basic and advanced ML methods including supervised learning and unsupervised learning.

During the second part, the connection between chemistry and mathematical tools of ML will be made and the concepts on the construction of loss functions, representations, descriptors and kernels will be introduced.

For the last part, experts who are actively using research methods to solve research problems in chemistry and materials will be invited to give real-world examples on how ML methods have transformed the way they perform research.

Target audience
  • Chemistry postgraduates
  • Further details regarding eligibility criteria are available
Sessions

Number of sessions: 8

# Date Time Venue Trainers
1 Tue 14 Jan 2020   13:00 - 17:00 13:00 - 17:00 Unilever Lecture Theatre Lucy Colwell,  Bingqing Cheng
2 Thu 16 Jan 2020   13:00 - 16:00 13:00 - 16:00 Unilever Lecture Theatre Lucy Colwell,  Bingqing Cheng
3 Tue 21 Jan 2020   13:00 - 14:00 13:00 - 14:00 Unilever Lecture Theatre Lucy Colwell,  Bingqing Cheng
4 Wed 22 Jan 2020   13:00 - 14:00 13:00 - 14:00 Pfizer LT Lucy Colwell,  Bingqing Cheng
5 Thu 23 Jan 2020   13:00 - 16:00 13:00 - 16:00 Unilever Lecture Theatre Lucy Colwell,  Bingqing Cheng
6 Tue 28 Jan 2020   13:00 - 14:00 13:00 - 14:00 Unilever Lecture Theatre Lucy Colwell,  Bingqing Cheng
7 Thu 30 Jan 2020   13:00 - 16:00 * 13:00 - 16:00 * Unilever Lecture Theatre Lucy Colwell,  Bingqing Cheng
8 Tue 4 Feb 2020   13:00 - 14:00 13:00 - 14:00 Unilever Lecture Theatre Lucy Colwell,  Bingqing Cheng
* Optional session.
Topics covered
  • Session 1: Basics in Probabilities, Statistics and Machine Learning + Workshop
  • Session 2: Regression, Classification and Prediction Part 1
  • Session 3: Regression, Classification and Prediction Part 2
  • Session 4: Guest Lecture
  • Session 5: Dimensional Reduction and Data Visualization + Workshop
  • Session 6: Making the Connection between Machine Learning and Chemistry Part 1
  • Session 7: Making the Connection between Machine Learning and Chemistry Part 2 + Optional Workshop
  • Session 8: Guest Lecture
  • Session 9: Guest Lecture
Bibliography
Theme
Machine Learning

Booking / availability