(2020) Machine Learning
Date: 21 - 22 September 2020
This workshop is intended to provide an introduction to machine learning and its application to bioinformatics. This workshop is not intended for machine learning experts. Instead it targets biologists or other life scientists who are wanting to understand what machine learning, what it can do and how it can be used for a variety of bioinformatic or medical informatics applications.
Prerequisites:
You will also require your own laptop computer. Minimum requirements: 1024×768 screen resolution, 1.5GHz CPU, 2GB RAM, 10GB free disk space, recent versions of Windows, Mac OS X or Linux (Most computers purchased in the past 3-4 years likely meet these requirements). If you do not have access to your own computer, please contact [email protected] for other possible options. Familiar with Linux or Unix operating systems, familiar with Python This workshop requires participants to complete pre-workshop tasks and readings.
Learning objectives:
Students will gain experience in: Applications and Limitations of Machine Learning and Deep Learning Data encoding for Machine Learning Artificial Neural Networks (ANNs) – how they work and how they can be used in bioinformatic applications (secondary structure prediction) ANNs – how to program a useful ANN for bioinformatics in Python Hidden Markov Models (HMMs) – how they work and how they can be used in bioinformatics applications (gene finding) HMMs – how to program a useful HMM for bioinformatics in Python Support Vector Machines, Decision Trees an Random Forests – how they work and how they can be used in bioinformatic applications (biomarker discovery and modeling) Using Machine Learning tools on the Web (WEKA) Using Machine Learning Apps (TENSORFLOW)
Capacity: 30
Event types:
- Workshops and courses
Instructors: David Wishart
Activity log
