Essex Summer School in Social Science Data Analysis 2024: Machine Learning for Estimating Treatment Effects from Observational Data
Led by MiSoC's Methods experts, this week-long summer school explores cutting-edge and established machine learning techniques
Led by MiSoC’s Professor Paul Clarke, Dr Damien Machlanski and Dr Annalivia Polselli, this week-long Summer School will cover various new and established machine learning techniques for prediction and causal effect estimation with observational data. We will start from the basics (e.g., Lasso, decision and boosted trees, random forest) and then move to more advanced topics (e.g., causal forest, meta-learners, neural-networks, double machine learning, hyperparameter tuning). Practical sessions will show how to apply these techniques with the statistical software R.
The course will take place from August 5th-16th at the University of Essex’s Colchester campus (or online if preferred).
(University of Essex PhD students attending can use Proficio funds to attend this course)
For more information, please visit the website below: https://essexsummerschool.com/summer-school-facts/courses/ess-2024-course-list/3b-machine-learning-for-estimating-treatment-effects-from-observational-data/
