Neural Architecture Search (Part II) - Lecture 8
Offered By: MIT HAN Lab via YouTube
Course Description
Overview
Explore neural architecture search techniques and their applications in this lecture from MIT's course on TinyML and Efficient Deep Learning Computing. Dive into hardware-aware neural architecture search, which considers hardware performance metrics like latency when designing neural network architectures. Learn about the joint optimization of hardware and neural architectures within a single search loop. Discover various applications leveraging neural architecture search, including the Once-For-All Network approach. Gain insights into efficient machine learning techniques for deploying powerful deep learning applications on resource-constrained devices such as mobile phones and IoT devices. Access accompanying slides and additional course materials to enhance your understanding of these cutting-edge concepts in efficient machine learning.
Syllabus
Lecture 08 - Neural Architecture Search (Part II) | MIT 6.S965
Taught by
MIT HAN Lab
Related Courses
TensorFlow Lite for Edge Devices - TutorialfreeCodeCamp Few-Shot Learning in Production
HuggingFace via YouTube TinyML Talks Germany - Neural Network Framework Using Emerging Technologies for Screening Diabetic
tinyML via YouTube TinyML for All: Full-stack Optimization for Diverse Edge AI Platforms
tinyML via YouTube TinyML Talks - Software-Hardware Co-design for Tiny AI Systems
tinyML via YouTube