Efficient Video Understanding and Generative Models - Lecture 19
Offered By: MIT HAN Lab via YouTube
Course Description
Overview
Explore efficient video understanding and generative models in this comprehensive lecture from MIT's 6.S965 course on TinyML and Efficient Deep Learning Computing. Delve into advanced techniques for deploying neural networks on resource-constrained devices like mobile phones and IoT devices. Learn about model compression, pruning, quantization, neural architecture search, and distillation for efficient inference. Discover methods for efficient training, including gradient compression and on-device transfer learning. Examine application-specific model optimization techniques for videos, point clouds, and NLP. Gain insights into efficient quantum machine learning. Access accompanying slides and course materials to enhance your understanding of these cutting-edge topics in machine learning efficiency.
Syllabus
Lecture 19 - Efficient Video Understanding and Generative Models | MIT 6.S965
Taught by
MIT HAN Lab
Related Courses
Digital Signal ProcessingÉcole Polytechnique Fédérale de Lausanne via Coursera Principles of Communication Systems - I
Indian Institute of Technology Kanpur via Swayam Digital Signal Processing 2: Filtering
École Polytechnique Fédérale de Lausanne via Coursera Digital Signal Processing 3: Analog vs Digital
École Polytechnique Fédérale de Lausanne via Coursera Digital Signal Processing 4: Applications
École Polytechnique Fédérale de Lausanne via Coursera