Machine Learning Meetup - Rome


The Rome Meetup was born in December 2016 with the aims of helping developers approach machine learning, connect people that work in the field, and provide an hub to spread ideas and events. With the support of Codemotion, LUISS EnLabs and several occasional sponsors, we organize monthly events with speakers from any background, from professors to managers, students, developers from several companies, and much more.

You can find us on Meetup, SlideShare, GitHub, and Facebook.

Past events

Below you can find a full list of the speakers we had at our past events. If you missed one, be sure to check out the slides and the codes! Most of the material here is in Italian.

Meetup #21 (October 2018)

Come sviluppare applicazioni intelligenti su larga scala con AWS (Alex Casalboni, Amazon) - [SlideShare]

Advanced analytics a supporto del marketing - Next best product (Giada De Berardinis & Giuseppe Campa, Crisma) - [SlideShare]

Meetup #20 (October 2018) - HiTalk Meetup: Creativity & Machine Learning

Modelli generativi: creare con il deep learning (Daniele Paliotta) - [SlideShare]

Data Driving Creativity e le sue applicazioni nel Marketing e nell'Advertising (Bruno Coletta, Payback Italia) - [SlideShare]

Meetup #19 (September 2018) - Politics & Deep Image Processing

Deep Image Processing (Mirko Lucchese & Marco Siciliano, Accenture) - [SlideShare]

Res Publica — Politicamente (s)corretto (Roberto Reale) - [SlideShare] [GitHub]

Meetup #18 (July 2018)

AI contro (Giovambattista Vieri, CEO di Ent s.r.l.) - [SlideShare]

Graph Analytics sulla community #Aperitech (Marco Liberati e Enrico Risa, GraphRM) - [SlideShare]

Meetup #17 (June 2018) - [Guest Meetup] Machine Learning @ Twitter & H2O

Sentiment Analysis on Tweets: how linear regression can be biased (Luca Belli, Twitter) - [SlideShare]

Introduction to Scalable & Automatic Machine Learning with H2O (Jo-fai Cho, H2O) - [SlideShare]

Meetup #16 (June 2018) - Learning UX & Data Science Applications

Learning user interfaces: the neural react component (Piero Savastano, Freelance) - [SlideShare]

DS4Biz - Data Science for Business (Fulvio D'Antonio, Live Tech) - [SlideShare]

Meetup #15 (May 2018) - AlphaGo & Adversarial Machine Learning

Adversarial examples in deep learning (Grégory Châtel, Disaitek and Intel Software Innovators) - [SlideShare]

(Alpha) Zero to Elo - with demo (Simone Totaro & Manuel Del Verme) - [SlideShare]

Meetup #14 (April 2018) - TensorFlow Dev Summit Viewing Party

TensorFlow eager execution and TensorFlow Lite (Simone Scardapane, Machine Learning GDE) - [SlideShare]

Meetup #13 (March 2018) - From Robotics to Neural Machine Translation!

How I built my robot with ROS and deep learning (Raffaello Bonghi, NTT Data) - [SlideShare]

Deep Learning for Machine Translation - A dramatic turn of paradigm (Alberto Massidda, Sourcesense) [SlideShare]

Meetup #12 (February 2018) - Artificial Intelligence Everywhere!

L'Intelligenza Artificiale al servizio del cittadino: #taskforceIA (Marco Bani, AgID) - [SlideShare]

Design in the age of artificial intelligence (Norman Di Palo) - [SlideShare]

Meetup #11 (January 2018) - KNIME & VR!

Your flight is boarding now (Vincenzo Tursi, KNIME) - [SlideShare]

Realtà Virtuale e Machine Learning (Enrico Speranza, SPVR Roma) - [SlideShare]

Introduzione a Unity Machine Learning (Gianluca Bombini, Oniride) - [SlideShare] - [GitHub demo forked from Unity]

Meetup #10 (December 2017) - Dal Vaticano ad Amazon!

Raiders of the lost review (Sara Di Bartolomeo) [Jupyter notebook on GitHub]

In Codice Ratio: deep learning applicato a documenti storici (Elena Nieddu, Roma Tre) - [SlideShare]

Meetup #9 (November 2017) - BabelNet & Economy

This Meetup was officially sponsored by BeMyApp and Intel.

Economic implications of Machine learning (Fabio Pelosin, Discontinuity) [SlideShare]

Enabling multilingual text analytics with BabelNet (Roberto Navigli, Sapienza) - [SlideShare]

Meetup #8 (October 2017) - Elasticsearch & Compre{n|s}sione

Compre{n|s}sione (Paolo Caressa, Codin) - [Reveal.js]

Anomaly Detection in ElasticSearch (Nicola Pagni, Seacom) - [SlideShare]

Meetup #7 (September 2017)

Quando le reti neurali inventano: tre esempi in TensorFlow (Simone Scardapane, IAML Co-Founder) - [] [GitHub demos]

Fuzzy Memory (Alberto Tono, BIMon)

Meetup #6 (July 2017) - Deep RL & General AI

Presentazione General AI Challenge (GoodAI)

Introduzione al deep reinforcement learning (Simone Totaro) - [SlideShare]

Meetup #5 (May 2017) /2 - Get Started with Deep Learning using Intel Tools

This Meetup was officially sponsored by BeMyApp and Intel.

Get Started with Deep Learning using Intel Tools (Mustafa Aldemir, Intel)

Meetup #4 (May 2017)

Deep learning e computer vision (Francesco Pugliese, ISTAT) - [SlideShare]

Vettori e parole: l'algebra del significato (Paolo Caressa, Codin) - [SlideShare] [Reveal.js version]

Meetup #3 (March 2017)

Algoritmi di apprendimento dinamico applicati allo sviluppo software (Marco Menichelli, XSense)

H20 - Sete di machine learning (Gabriele Nocco, IAML Co-Founder) - [SlideShare]

Meetup #2 (March 2017) - TensorFlow Dev Summit Extended

No material available - check out the featured videos from the Dev Summit itself!

Meetup #1 (February 2017) - Meetup Introduttivo

AI for business: Capire l'opportunità (Gianluca Mauro, AI Academy) - [SlideShare]

Serverless Data Architecture at scale on Google Cloud Platform (Lorenzo Ridi, Noovle) - [SlideShare]