DSF Meetup with Peak.ai
Charlotte St, Manchester M1 4ET, UK
Join the Data Science Festival Manchester in partnership with Peak.ai for 2 epic talks this September.
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 on September 17th 2019, the ballot will be drawn on the 13th September 2019. Those randomly selected will then be e-mailed a Universe ticket for the event.
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.
6:00pm: Doors open
6:30pm: Tom Preece
7:45pm: Robin Lester
Tom Preece - Model Interpretability: Unboxing Black-Boxes using Game Theory
Summary: This talk will focus on model agnostic methods to interpret black-box models and explain why it is making predictions.
Bio: Tom Preece is a Data Scientist at Peak, he has led and delivered several Data Science projects for Peak. Prior to that he has experience working in Hanoi and Shanghai, executing projects for clients across Asia and North America. Tom’s current Data Science interests revolve around machine learning interpretability and sequence modelling.
Robin Lester - Training and operationalizing your ML models in Azure.
Summary: In this talk we will take a tour of the Azure Machine Learning Service to train and deploy a machine learning model.Technologies we will cover are: - Azure Machine Learning Service - Azure Machine Learning SDK for Python - Microsoft Azure Notebooks - Azure Container Instances - AutoML - Azure Machine Learning Service Visual Interface
Bio: Robin Lester is a Cloud Solutions Architect (CSA) at Microsoft in One Commercial Partner (OCP). Working in the industry for over 20 years, focusing on data tools such as SQL Server and AI technologies. Having worked as both a Premier Field Engineer and a CSA at Microsoft Robin has a deep technical background in everything related to Data and AI.