DSC140B: Representation Learning (SP24)

Representation learning is widely used in data science and machine learning. This course will introduce basic concepts of representation learning and machine learning algorithms involving representation learning. This course will serve as a foundation for research and engineering in machine learning and data science.

Course Contents

• Fundamentals (linear algebra)
• Unsupervised Learning (principal component analysis, laplacian eigenmaps)
• Supervised Learning (feature map, radial basis function, neural networks)
• Modern Representation Learning and Deep Learning

Course Staff

• Instructor: Prof. Lily Weng, HDSI
• TA:
  • Somanshu Singla, CSE
  • Yashowardhan Shinde, ECE
  • Yilan Chen, CSE

For contact information, see Staff page.

Course Logistics

For course logistics, see Logistics page.

Course Timeline

For course timeline, slides, and scribe-notes, see Course Timeline page.