Course Detail
Units:
3.0
Course Components:
Lecture
Description
This course is an applied introduction to deep learning, a branch of machine learning, that aims to understand and practice the development and application of modern neural networks. In that vein, the course will provide students with a working knowledge of deep learning fundamentals that presents a start point for using more advanced techniques in their future careers. The course will start by reviewing and implementing the main mathematics, statistics, and machine learning principles that will be required during the course. Then, the students will learn how deep learning algorithms extract layered high-level representations of data in order to optimize feature learning, cluster analysis, and classification machine learning tasks. Hands-on activities will provide students with the experience of implementing deep learning architectures for mainly biomedicine applications.