Bologna (Italy) - January 25, 2019
Ex Machina
All Machine Learning. No fluff.

Ex Machina is a one-day event for Machine Learning practitioners. We’re going to shed the hype and focus on the pragmatic stuff: how Machine Learning works in practice, how companies are using it, and how you can apply it today. We’ll have a few talks, and plenty of time for an open space discussion.

We'll start at 9:30 and finish at 18:00. We'll have talks in the morning, and plenty of time for an Open Space in the afternoon. We also have social events on the night before, if you're already in Bologna.

From deep learning to chatbots, Machine Learning is changing the world. Be a part of that change.*

* Well, a little bit of hype is OK.


Social Events on Thursday 24

VIEW THE SLIDES FROM THE FIRST EVENT!
MORNING FROM 9:30: TALKS
Not on my (Neural) Watch: Automatic Detection of Hate Speech in Social Media
Valerio Basile

Natural Language Processing has been used in machine learning for years. The explosion of social media has shifted the focus back to written natural language, and comes with many new ethical, social, and practical issues.

One such issue is the widespread diffusion of hate speech on social media platforms, and how to counteract it. In this talk, I will give an overview of the NLP approaches to hate speech detection, from the earliest methods based on dictionaries and support vector machines, to the new ones based on recurrent neural networks and word embeddings. I’ll show how to recognize hate speech from loosely labeled data. I will also showcase the first results of a current research project aimed at mapping the hate speech in Italy using data from Twitter.

Machine Learning per la Moderazione di Commenti
Marco Radossi

Cosa succede quando sei un editore e devi vagliare 9k commenti al giorno? Principalmente un aumento di caffeina nel sangue del tuo staff e una crescita esponenziale degli errori di moderazione. In questo talk illustreremo un case study su come abbiamo introdotto (e sperimentato) il machine learning (NLP) per la moderazione dei commenti a supporto dello staff editoriale.

Machine Learning in Wastewater Treatment Plants
Luca Pucci, Dario Torregrossa

Urban Wastewater Treatment Plants (WWTP) remove contaminants from municipal wastewater, that contains household sewage and industrial wastewater. They are dynamic and complex systems, because of the continuous variations of wastewater characteristics and the intrinsic complexity of biological processes.

To work effectively and efficiently, these processes require a proper level of dissolved oxygen to support aerobic bacteria. The level of oxygen is measured by DO sensors, that are exposed to high risk of failures because of the wastewater pollutants. In this talk, we tell how we used neural networks to identify sensor anomalies as soon as they happen.

Machine Learning in the Cloud
Gianluigi Mucciolo

Difficilmente la tua azienda è unica al mondo. Hai dei concorrenti, che magari forniscono gli stessi tuoi servizi. Ciononostante, molte aziende usano soluzioni AI custom invece di investigare le soluzioni che sono già disponibili.

L’Intelligenza Artificiale richiede grandi investimenti. Non innovare… riutilizza! Vedremo quali soluzioni cloud sono sul mercato, le tecnologie disponibili, e come possiamo riutilizzare ciò che già abbiamo. Descriveremo poi una nostra esperienza concreta che riguarda la news recommendation, mostrano come i servizi di AWS hanno semplificato il processo di deploy e la validazione della soluzione.

Neural network design
Anna-Chiara Bellini

Come faresti a progettare un neural network da zero, per un problema specifico?

AFTERNOON UNTIL 6pm: OPEN SPACE

We'll collect Open Space topics on the spot. If you wish, you can send an early topic proposal. A few ideas:

  • How you used Machine Learning in production. The domain doesn’t matter: e-commerce, business intelligence, healthcare… We’re curious about them all.
  • No production system to speak of? Then you can tell us about your pilot, prototype, or anything–as long as it’s up and running.
  • Tutorials. Yes, we prefer concrete examples–but it’s hard to say no to a great tutorial.

We’ll pick additional topics on the spot, as per the open space rules.

How do I get there?