Introduction to Machine Learning in Biomedical Research

Content

• Introduction to Data Analysis and Machine Learning 
• Data wrangling, testing methods, etch 
• Classic Machine Learning approaches, such as logistic regression, support vector machine, random forest 
• Introduction to Python for data analysis and machine learning (numpy, pandas, Scikit- learn) 
• Exercises in classic Machine Learning 
• Neural Network, including feed-forward network for biomedical data 
• Small group projects with real data 
• Groups present projects 
• Example applications in the biomedical field. Seminars by invited speakers.

Learning Outcome

A student who has met the objectives of the course will be able to: 

• Understanding basic concepts in Machine Learning  
• Understand the impact of data on Machine Learning outcomes 
• Apply Machine Learning to biological and medical datasets 
• Apply Python Machine Learning modules  
• Evaluate the performance of Machine Learning system 
• Disseminate the project result in a technical report