Course Overview
This course has been designed and developed for providing knowledge about the Fundamentals of TinyML. It provides hands-on experience using Tensorflow Lite to build deep learning solutions for embedded and low-powered devices along with. The course also focuses on responsible AI design and building various applications of TinyML.
Who should attend
- Software Engineers
- Software Developers
Prerequisites
Attendees should preferably have basic knowledge of Unix commands and Basic Programming Knowledge of Python. The attendees should also know Machine Learning, Deep Learning and Tensorflow framework.
Outline: Fundamentals of TinyML (FTML)
Welcome to TinyML
- Course Introduction
- The Future of ML is tiny and bright
- TinyML Challenges
- Getting Started
Introduction to Tensorflow Lite
- Introduction to Tensorflow Lite and Micro
- Model Optimisation
- TFLite Micro Benchmarks
- Module Recap
Introduction to (Tiny)ML
- The Machine Learning Paradigm
- The Building Blocks of Deep Learning
- Exploring ML Application
- Building a TinyML Model
- Summary