This repository contains all the assignments from the course Machine Learning for IoT.
The course aims to introduce the problems related to the implementation of machine learning applications and algorithms on platforms other than high-performance servers available in the cloud.
The course topics are organized in three main parts:
- Internet-of-Things,
- Machine and Deep Learning in the IoT,
- Data exchange.
Technologies adopted: Tensorflow, Pytorch, Keras, CherryPy
| Topic | Repository Link | |
|---|---|---|
| HW1 | VAD Optimization and Memory Constraint Time-Series Processing | link |
| HW2 | Training and Deployment of a "Go/Stop" Words Classifier | link |
| HW3 | Data Collection, Communication and Storage | link |
A.Y. 2022/23
All credits to the professor of the course Calimera Andrea, and the TAs Peluso Valentino et al.