ML_for_Chem

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The course materials for Cambridge's Machine Learning for Chemistry

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# Course Materials Site for Machine Learning for Chemists
Hello All!  Thank you for taking the time out of your day to be guinea pigs for this course. I'll be uploading the Live Demos, a worked through demo (should I run out of time or forget something at the end of the lecture) and the lecture slides for each course.

~~The lecture recordings will likely be handled by Chung Tu ct465[at]cam.ac.uk.~~

**UPDATE 5 FEB 2024:** Lecture recordings will be uploaded to the Lecture_Recordings folder.

**UPDATE 19 FEB 2024** We are a bit behind schedule for those who are following the repo. Lecture 2's materials (12 Feb) were covered over 2 sessions. Hence the live demo for Lecture 2 was covered on 19 Feb instead of 12 Feb.

**UPDATE 26 FEB 2024** This [link](https://distill.pub/2019/visual-exploration-gaussian-processes/) takes you to the interactive Gaussian Processes. Apologies for those attending virtually, we had some technical difficulties today and some of the lecture was not recorded. Feel free to email me with any questions.

**UPDATE 27 FEB 2024** The [dataset that we are using](https://github.com/doylelab/rxnpredict/blob/master/data_table.csv) in the live demos (and preworked demos) has now been uploaded to the Live_Demos and Preworked_Demo folders.

If any of you would like to get in touch with me, please feel free to email at: esk34[at]cam.ac.uk.

**UPDATE 4 MAR 2024** That's all from me!  Thank you, everyone!

ML_for_Chem

ML_for_Chem Latest Version Download

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