ivanovitchm/seminar_tinyml

Seminar - TinyML and Internet of Intelligent Vehicles

Seminar for DRII Ph.D. Students

References

• 📚 Pete Warden and Daniel Situnayake. TinyML Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers [Link]
• 🏫 Vijay Janapa Reddi; Laurence Moroney; Pete Warden. Professional Certificate in Tiny Machine Learning [Link]
• 📃 Signoretti, G.; Silva, M.; Andrade, P.; Silva, I.; Sisinni, E.; Ferrari, P. An Evolving TinyML Compression Algorithm for IoT Environments Based on Data Eccentricity. Sensors 2021, 21, 4153. [Link]
• 📃 Andrade, P.; Silva, I; Signoretti, G.; Silva, M.; Dias, J.; Marques, L.; Costa, D. An Unsupervised TinyML Approach Applied for Pavement Anomalies Detection Under the Internet of Intelligent Vehicles. Metroind40iot, Roma, 2021. [Link]
• 📃 Silva, M.; Vieira, E.; Signoretti, G.; Silva, I.; Silva, D.; Ferrari, P. A Customer Feedback Platform for Vehicle Manufacturing Compliant with Industry 4.0 Vision. Sensors 2018, 18, 3298. [Link]
• 👍 Introduction to Embedded Machine Learning [Link]
• 📣 This is a list of interesting papers, projects, articles and talks about TinyML [Link]

The Internet of Intelligent Vehicles and Their Applicatons [Slide]

• Introduction & Presentation [Video]
• Trends & Motivations [Video]
• Taxonomy of Connected Vehicles (Soft) [Video]
• Taxonomy of Connected Vehicles (Hard) [Video]
• All roads lead to edge computing [Video]
• The future is tiny [Video]
• Final recap [Video]

TinyML - the convergence between Machine Learning and the IoT [Slide]

• TinyML Motivation [Video]
• TinyML Fundamentals [Video]
• Why the future of ML is tiny and bright? [Video]
• How do we enable TinyML? [Video]

TinyML Challenges [Slide]

• Challenges from a hardware perspective [Video]
• Challenges from a software perspective [Video]
• Challenges from ML perspective [Video]
• Challenges from ML pipeline [Video]

Python Fundamentals for TinyML

• Google Colab introduction [Video]
• Python Crash Course
• Introduction to Pandas
• Exploring data with Pandas
• Data Cleaning Basics
• Functions, Context Managers and Decorators
• Object-Oriented, Functional Programming
• TensorFlow 2.x + Keras Crash Course
• Introduction to TF

Applications of TinyML

AI Lifecycle and ML Workflow [Slide]

• AI lifecycle [Video]
• ML workflow [Video]

Machine Learning on Mobile and Edge IoT Devices

• Introduction to TensorFlow Lite
• Using the TFLite Converter
• Running Models with TFLite
• TFLite Optimizations and Quantization
• Quantization Aware Training
• Post Training Quantization (PTQ)
• Quantization Aware Training (QAT)
• Inference Engine: TF vs. TFLite