CSC/EE 8001: Designing End-to-End ML Systems
Lectures: Wednesday noon-2:50PM in Naka 222
Instructor: Tanu Malik
Email: tanu [at] missouri.edu
Office Hours: Tuesday 5-6pm CT @ Naka 311
Announcements
- [2025-08-29] Assignment 1 released on Canvas; see due date under Schedule.
- [2025-08-26] Office hours: Tuesday 5:00PM-6:00PM Naka 311. Please additionally send me email if you plan to meet on Zoom.
Course Goals
This is a research-based course on systems for machine learning (ML), and lies at the intersection of the fields of ML/AI, data management, and systems. Students will learn about the landscape and evolution of ML systems and the latest research. This course will cover key systems topics including systems for scalable ML model building, data sourcing and preparation for ML, ML platforms, and issues in ML deployment and MLOps. A major component of this course is a course project on MLOps and reviewing research papers on these topics. The course is currently for MS students and PhD students.
Schedule
| Date | Details | PDFs |
|---|---|---|
| Machine Learning (ML) & ML systems overview | — | |
| Loss functions, Gradient Descent, Bias-Variance, ML development cycle | - | |
| Neural Networks and Large scale ML systems | — | |
| Cloud Computing and DevOps for ML | — | |
| Data Selection | — | |
| Model Performance and Model Evaluation/ | — |