Directed Reading: Applied Deep Learning
- Course Number
- CHL7001H S1
- 7000 (Reading Courses & Research Projects)
- Course Instructor(s)
- Jodie Zhu
The course will introduce practical and theoretical methodologies for applying deep learning to practical applications, including public health sciences, based on techniques employed in realworld contexts. Students will acquire familiarity with the fundamental organizational and technical requirements that need to be considered when putting deep learning applications into practice. The course will cover tensorflow, data preparation, model selection, model evaluation, advanced model architectures, debugging, infrastructure, model deployment, and ML in practical applications. The course will also review machine learning fundamentals and relevant theory. Upon completion, students will be able to develop and deploy systems that leverage machine learning in public health projects.
By the end of the course students will be able to:
- understand how to best apply and evaluate machine learning models for research and
- build and deploy systems that leverage machine learning to achieve goals;
- set up and maintain an ML development infrastructure to improve efficiency and
shorten project timelines.
Methods of Assessment
For more detailed information, please visit the course web page.