SciTinyML: Scientific Use of Machine Learning on Low-Power Devices will be run remotely in English for 2023 from April 17-21.
SciTinyML is an ICTP Virtual Meeting supported by the TinyML4D Academic Network and open to all.
TinyML is a subfield of Machine Learning focused on developing models that can be executed on small, realtime, low-power, and low-cost embedded devices. This allows for new scientific applications to be developed at an extremely low cost and at large scale.
The TinyML process starts with collecting data from IoT devices, then training the collected dataset to extract knowledge patterns; these patterns are then packaged into a TinyML model that considers the target microprocessor’s limited resources such as memory and processing power. The resulting model is then deployed on embedded devices where it is used to evaluate new sensor data in real-time. Typically, power requirements are in the mW range and below which enables a variety of use-cases targeting battery operated devices. TinyML represents a collaborative effort between the embedded power systems and Machine Learning communities, which traditionally have operated independently.
- ML general concepts
- Introduction to TinyML
- Getting started with the TinyML training kit
- Examples of TinyML applications
- Scientific Applications of ML
- Recent Research and Applications in TinyML
Full Schedule Table Coming Soon!
Contact firstname.lastname@example.org with any questions regarding this workshop.