Pixel Proficiency: Practical Deep Learning for Images

Session Dates: Oct 15 - Nov 19, Wednesdays from 12:30-1:50 p.m.

In-person and zoom options available. While we offer a remote option, we encourage in-person participation, when possible.

The series of 6 tutorials will demonstrate how to build neural networks capable of addressing common computer vision tasks such as classifying patterns in images, detecting objects, identifying the boundaries of those objects. These tutorials will be focused on providing more than just a brief introduction to technical tools; attendees will also learn methods to rigorously validate the accuracy of their models and assess how their results generalize in the presence of new data. We will focus on convolutional network architectures and will teach the skills to adopt more complex ones through the Python Keras library.

Participant Expectations: No prior experience with neural networks or related software packages is necessary, though attendees are expected to have some basic experience with Python code and should have some familiarity with one or more basic machine learning approaches, such as logistic regression or random forests. Attendees will use the Keras library to do their work, but learn concepts that are broadly useful regardless of the technology.

PLEASE NOTE: This event is a series of 6 tutorials held over 6 weeks. One $10 ticket for the first date covers all sessions. Due to limitations of the Eventbrite platform only the first session will populate to your calendar. Please make sure to mark your calendar accordingly.