About
Machine learning (ML) extracts knowledge from data and focuses on prediction. ML learns from our data how to make decisions for future observations. It is widely used and common in everyday interactions – on Facebook, Google, Amazon, or your favorite automated teller machine (ATM). Equally important are applications in science, such as personalized cancer treatment, medical diagnoses, and drug discovery. ML is essential in data driven sciences.
This machine learning workshop series is composed of 4 sessions of hands-on practice spanning February 13th - 21st, and is aimed at graduate students and other researchers who would like to learn more about machine learning for biomedical data. This workshop is open to those from neighboring institutions.
At the end of this course, participants will be able to:
- Describe the types of machine learning
- Describe the basics of supervised learning
- Build regression, classification, and clustering models to model data
- Apply and evaluate a machine learning algorithm
Participants should be competent with Python and the basics of Pandas and NumPy libraries. Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.). They should have the most recent version of Python installed.
Python is a popular language for research computing, and great for general-purpose programming as well. Installing all of its research packages individually can be a bit difficult, so we recommend Anaconda, an all-in-one installer.
Regardless of how you choose to install it, please make sure you install Python version 3.x (e.g., 3.6 is fine).
We will teach Python using the Jupyter Notebook, a programming environment that runs in a web browser (Jupyter Notebook will be installed by Anaconda). For this to work you will need a reasonably up-to-date browser. The current versions of the Chrome, Safari and Firefox browsers are all supported (some older browsers, including Internet Explorer version 9 and below, are not).
For additional information please visit the workshop website.
