Workshops

Students will gain experience in: Applications and Limitations of Machine Learning and Deep Learning Decision Trees and Random Forests – how they work, how they are coded in Python, and how they can be used in bioinformatic applications (biomarker discovery and modeling) Applications and Limitations of Machine Learning and Deep Learning Decision Trees and Random Forests – how they work, how they are coded in Python, and how they can be used in bioinformatic applications (biomarker discovery and modeling) Artificial Neural Networks (ANNs) – how they work, how data is encoded, how they are coded in Python, and how they can be used in bioinformatic applications (classification and secondary structure prediction) Fundamentals of clustering as an unsupervised machine learning method Machine learning operations principles.