EfficientML.ai - Quantization Part II - Lecture 6
Offered By: MIT HAN Lab via YouTube
Course Description
Overview
Dive into advanced quantization techniques in this comprehensive lecture from MIT's 6.5940 course on Efficient Machine Learning. Explore the intricacies of quantization methods, their impact on model performance, and strategies for optimizing neural networks. Learn from Professor Song Han as he delves into the second part of quantization, building upon fundamental concepts to address more complex challenges in efficient machine learning. Gain valuable insights into state-of-the-art approaches for reducing model size and computational requirements without sacrificing accuracy. Enhance your understanding of efficient ML techniques and their practical applications in real-world scenarios.
Syllabus
EfficientML.ai Lecture 6 - Quantization Part II (MIT 6.5940, Fall 2024)
Taught by
MIT HAN Lab
Related Courses
Optimize TensorFlow Models For Deployment with TensorRTCoursera Project Network via Coursera Jetson Xavier NX Developer Kit - Edge AI Supercomputer Features and Applications
Nvidia via YouTube NVIDIA Jetson: Enabling AI-Powered Autonomous Machines at Scale
Nvidia via YouTube Jetson AGX Xavier: Architecture and Applications for Autonomous Machines
Nvidia via YouTube Streamline Deep Learning for Video Analytics with DeepStream SDK 2.0
Nvidia via YouTube