We are happy to announce the 35th PyData Cambridge meetup! This is our second in person meetup since the pandemic started and we are happy to welcome everyone back!

Starting from September onwards we will need organisers to help with our meetup. Our code of conduct has always reflected the diversity we want in our meetup. To continue this and improve our meetup this has to start by changing things at the top. So we especially would like to welcome organisers coming from a more diverse background.

Please keep in touch with us on meetup or our email:
pydatacambridge@gmail.com

Many thanks to Raspberry Pi, who help us host the meetup.

Agenda

18:45 - Doors open
19:00 - Introduction
19:10 - "TinyML" (talk) by Gian Marco Iodice, Arm
19:55 - Interval
20:15 - (Second slot is waiting for confirmation)
21:00 - End (Pub - Old Ticket Office, Station Square)

Code of Conduct

PyData is dedicated to providing a harassment-free event experience for everyone, regardless of gender, sexual orientation, gender identity, and expression, disability, physical appearance, body size, race, or religion. We do not tolerate harassment of participants in any form.

The PyData Code of Conduct governs this meetup. ( http://pydata.org/code-of-conduct.html ) To discuss any issues or concerns relating to the code of conduct or the behaviour of anyone at a PyData meetup, please contact NumFOCUS Executive Director Leah Silen (leah@numfocus.org) or organizers.

Talks

**TinyML
**By Gian Marco Iodice

Abstract
TinyML is attracting interest across various industries for the massive opportunity to bring machine learning to low-power devices, such as microcontrollers. This technology is already around us and promises to make AI ubiquitous for Good. For example, TinyML is improving automation and resource efficiency usage in industrial and agriculture fields and allowing the monitoring of our health with smartwatches, just to name a few. By nature, TinyML is a multidisciplinary technology. Therefore, we require knowledge from different domains to build practical TinyML-based applications. In this workshop, Gian Marco will give an overview of TinyML and its critical concepts about machine learning (ML) and microcontrollers.

He will start by talking about the importance of TinyML and why it is now an attractive field. The second part will highlight the main challenges when deploying smart applications on memory-constrained devices. In the end, he will give an overview of the possible applications in the TinyML space.

Bio
Gian Marco Iodice is a tech lead in the Machine Learning Group at Arm and author of the TinyML Cookbook, published in April 2022. At Arm, Gian Marco looks after the ML performance optimisations for the Arm Compute Library, which he co-created in 2017 to get the best performance on Arm Cortex-A CPUs and Mali GPUs. Arm Compute Library is currently the most performant library for ML on Arm, and it’s deployed on billions of devices worldwide – from servers to smartphones.

Gian Marco holds an MSc, with honors, in electronic engineering from the University of Pisa (Italy) and has several years of experience developing ML and computer vision algorithms on edge devices. In 2020, Gian Marco co-founded the TinyML UK meetup group to encourage knowledge-sharing, educate, and inspire the next generation of ML developers on tiny and power-efficient devices.