🗣️ About the Event: Dive into the world of Machine Learning with a special focus on mental health data analysis! This workshop serves as your gateway to understanding and appraising machine learning in mental health research. Whether you’re planning to apply machine learning techniques yourself or working alongside those who do, this workshop is designed for beginners and curious learners.
🔍 What to expect: You’ll start from the fundamentals and progress to running a basic machine learning analysis on synthetic mental health data. The workshop covers cross-validation strategies, data pre-processing, and basic algorithms like decision trees and logistic regression, coded from scratch in R. We’ll address unique challenges in mental health data and explore effective machine learning applications in this field.
🎯 Who should attend: Researchers, practitioners, and professionals interested in machine learning and mental health data analysis. This workshop is suitable for those with varying levels of experience, including beginners.
About the Instructor: Marcos Del Pozo Banos is a senior lecturer at Swansea University Medical School. Marcos has over 10 years of experience applying machine learning to a wide range of biometric problems in the fields of security, biology, and medicine. His research focuses on the analysis of routinely collected electronic health records for the study of suicide and self-harm prevention, applying advanced machine learning techniques alongside traditional epidemiological methods.
- Self-Paced Learning:
- Gain access to comprehensive video lessons covering all theoretical concepts prior to the workshop. View these materials at your convenience to prepare for the in-person session.
- In-Person Session:
- Swift review of self-paced material, followed by interactive Q&A.
- Delve into practical coding sessions in R, constructing basic machine learning algorithms.
- Conduct hands-on analysis using synthetic mental health data.
- Discussion on best practices for applying machine learning in mental health research.
- Post Workshop Online Q&A Session:
- Address queries from self-paced learning or the in-person session.
- Platform for further discussion and clarification.
- No prior machine learning knowledge required.
- Basic familiarity with R is beneficial but not mandatory.
- Approach focuses on intuition, minimizing complex mathematics.
🍽️ Lunch provided; attendees must register dietary requirements by 8th April.
📷 Note; photos will be taken throughout the event for promotional purposes.
📝 Abstract Submission: Researchers interested in presenting their work at the