EVENT - Tuesday
Location40 Molesworth St, Dublin, Ireland
When6:00 PM - 9:00 PM
DSF Meetup with Walmart Labs
Join Data Science Festival – Dublin in partnership with Walmart Labs this October for two great speakers.
Due to the popularity of Data Science Festival events, we are now allocating event tickets via a random ballot. Registering here enters you into the ticket ballot for the Data Science Festival Event at Walmart Labs on October 22nd 2019, the ballot will be drawn on the 18th October. Those randomly selected will then be e-mailed a Universe ticket for the event, with the joining details.
If you get an allocated Universe ticket, please bring a copy of your paper ticket or your ticket on your phone to the event to check in with your QR code. Tickets are non-transferable.
PLEASE NOTE REGISTERING ON MEETUP DOES NOT GUARANTEE YOU ENTRY TO THIS EVENT.
Please click here to apply for a ticket: GET TICKETS
6:00: Doors open
6:30: Mirko Arnold
7:45: Guglielmo Iozzia
Mirko Arnold – Computer Vision Engineer, Intelligent Retail Lab by Walmart
Summary: The Tensorflow Object Detection API is a flexible framework for training deep learning models for object detection in images. This talk is intended as a tutorial giving an overview of the capabilities of the API and explaining ways to train, evaluate, modify and export object detection models. It will touch on topics such as model fine-tuning, data augmentation and training on GPUs and Google’s AI platform.
Bio: Mirko is one of the first engineers to join Walmart’s Intelligent Retail Lab in Dublin where his focus is on applying deep neural networks and classical computer vision methods in retail environments. He holds a PhD from Trinity College Dublin and has a background in machine learning, computer vision and signal processing. Before joining IRL he has worked in various R&D roles in industrial machine vision and the medical device industry.
Guglielmo Iozzia – Associate Director – Business Tech Analysis, IT and Analytics presso MSD
Summary: Predicting Apache Spark apps performance through Optimal Experiment Design, Machine Learning and Deep Learning