Machine Learning Hardware & Systems | Cornell ECE 5545 | Spring 2022

Explore the hardware and systems aspects of machine learning with this comprehensive course by Prof. Mohamed Abdelfattah. Gain insights into deep neural network computations, hardware accelerators, and real-world ML deployment.

Introduction

This course provides an in-depth exploration of the hardware and systems aspects of machine learning, covering topics such as deep neural network computations, hardware metrics and roofline analysis, hardware accelerators, and system-level considerations for deploying machine learning models.

Highlights

• Comprehensive coverage of machine learning hardware and systems
• Taught by Prof. Mohamed Abdelfattah, an expert in the field
• Hands-on projects and assignments to reinforce learning
• Insights into the latest advancements and challenges in ML hardware and systems

Recommendation

This course is highly recommended for students and professionals interested in the intersection of machine learning and computer hardware. It provides a solid foundation for understanding the technical aspects of deploying machine learning models in real-world systems.

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