YoVDO

TinyEngine and Parallel Processing - EfficientML.ai Lecture 11

Offered By: MIT HAN Lab via YouTube

Tags

Machine Learning Courses Embedded Systems Courses Microcontrollers Courses Code Generation Courses Edge Computing Courses Parallel Processing Courses Model Compression Courses TinyEngine Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore the intricacies of TinyEngine and parallel processing in this comprehensive lecture from MIT's 6.5940 course on Efficient Machine Learning. Delve into advanced concepts presented by Prof. Song Han as he discusses the implementation and optimization of TinyEngine for resource-constrained devices. Learn about parallel processing techniques that enhance the performance of machine learning models on edge devices. Gain valuable insights into the latest developments in efficient ML deployment and understand how TinyEngine contributes to the field of embedded AI. Access accompanying slides for visual aids and additional resources to supplement your learning experience.

Syllabus

EfficientML.ai Lecture 11 - TinyEngine (MIT 6.5940, Fall 2024)


Taught by

MIT HAN Lab

Related Courses

TensorFlow Lite for Edge Devices - Tutorial
freeCodeCamp 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