AI Tech Suite

Efficient AI Computing

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About

Efficient AI Computing focuses on techniques necessary for deploying deep learning applications on everyday devices while addressing computation demands. The course covers model compression, pruning, quantization, neural architecture search, and distributed training, as well as application-specific methods for optimizing large language models and diffusion models. Students gain hands-on experience with implementing these techniques and deploying models like Llama2-7B. Lectures, office hours, and assignments are outlined to ensure effective learning, while prerequisites ensure students are adequately prepared for the coursework.

Platform

Keywords

machine learning deep learning model optimization efficient ai resource-constrained

Task

machine learning

Features

• model compression

• pruning

• quantization

• neural architecture search

• distributed training

• on-device fine-tuning

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