Deep Learning In The Classroom
SIGCSE '18: Proceedings Of The 49th ACM Technical Symposium On Computer Science Education
This workshop is a hands-on exploration of Deep Learning techniques and topics for use in the classrooms of Computer Science and related fields. Deep Learning denotes the latest in a series of advances in neural network training algorithms and hardware that allow Artificial Neural Networks (ANNs) to learn quickly and effectively, even with many, stacked layers. These types of networks can be applied to almost any learning problem, such as driving a car, describing images, controlling a robot, or understanding language. This workshop will start with the mathematical and algorithmic foundations of Deep Learning, and introduce an accessible Python-based library, called "conx," which is based on the Keras library and was developed by the workshop instructors. The workshop will demonstrate ideas through animation and visualizations, examine the path to advanced topics, and explore ideas for incorporating Deep Learning topics into the classroom. The workshop is designed to allow participants to gain a foothold with these complex topics, and to help them develop their own materials for teaching. Workshop materials will be made freely available before the workshop as Jupyter notebooks.
Association for Computing Machinery
SIGCSE '18: The 49th ACM Technical Symposium On Computer Science Education
February 21-24, 2018
D. S. Blank, Lisa A. Meeden, and J. Marshall.
"Deep Learning In The Classroom".
SIGCSE '18: Proceedings Of The 49th ACM Technical Symposium On Computer Science Education.