About
Statistics 654: Introduction to Applied Deep Learning (2 units)
Course Description:
Introduction to neural networks and deep neural networks, training a prediction model, avoiding over-fitting, tuning. Prediction and classification problems. Using R packages or Python to connect to h20, tensorflow, keras. Report Writing.
Prerequisites:
Post-baccalaureate standing.
Possible Instructional Methods:
Entirely On-ground, or Entirely Online, or Hybrid.
Grading:
A-F or CR/NC (student choice).
Student Learning Outcomes
Upon successful completion of this course students will be able to:
- Use software to learn from data.
- Critically evaluate learning models.
- Extract data from large data source to learn from data.
- Create reproducible reports.