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LinkedIn Learning

Learning TinyML

via LinkedIn Learning

Overview

Prepare for a new career with $100 off Coursera Plus
Gear up for jobs in high-demand fields: data analytics, digital marketing, and more.
Learn the basics of TinyML, the field of machine learning that enables ML applications to run on handheld and IoT devices.

Syllabus

Introduction
  • Getting started with TinyML
  • What is TinyML?
  • What you should know
1. Is Your Problem a TinyML Problem?
  • Defining constraints
  • Checklist for a TinyML problem
2. Solving the Constraints: Optimization Techniques
  • Pre-trained models
  • Quantization and types of quantization
  • TFLite post training quantization
  • Quantization awareness training in TFLite
  • Pruning
  • Knowledge distillation
  • Challenge: Compare results of optimization
  • Solution: Compare results of optimization
3. Deploying TinyML Models
  • Edge impulse
  • Deploy a classification project to your phone
  • Challenge: Deploy a regression model to your phone
  • Solution: Deploy a regression model to your phone
4. TinyMLOps
  • Hardware devices
  • Bringing all the concepts together
Conclusion
  • Resources for TinyML
  • Future of the TinyML: Research directions
  • Next steps with TinyML

Taught by

Vaidheeswaran Archana

Reviews

4.6 rating at LinkedIn Learning based on 25 ratings

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