online course
MIT 6.5940 TinyML and Efficient Deep Learning Computing
This course focuses on efficient machine learning and systems, introducing techniques that enable powerful deep learning applications on resource-constrained devices.
Keywords: LLM inference, TinyML, distributed training, efficient deep learning, model compression, neural architecture search, pruning, quantization
Competency level: ••• Advanced
Target audience: Graduate-level students with computer architecture and intro ML background
Resource type: online course
Status: Active
Prerequisites:
MIT 6.191 Computation Structures and 6.390 Intro to Machine Learning (or equivalent prior experience)
Date created: 2024-09-05
Contributors: MIT (Prof. Song Han, HAN Lab)
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