This meeting includes talks from experts and allows you to learn about the basics of using machine learning (ML) and get hands on experience through the use of git repository of introductory machine learning examples. You will get to discuss ML with the experts, and through pre-session reading material will learn about the process of using ML with data.
We will be using the V2.0 tag of this repository that is the release used for this GRADnet ML 2021 meeting.
We will be using binder to work with the code examples. This will ensure that you don't have to set up the code environment to get started with machine learning. Click on the following link to launch the binder page for this tutorial:
WARNING: Some of the more complicated models will take a long time to learn, and for those the point of including them is to provide you with the examples to work with in your own time after the envent.
PRE-SESSION READING: If you would like to learn more about the machine learning methods in this tutorial, then please see the material posted just below. These slides cover a number of concepts that underpin some of the algorithms used in the tutorial, and provide background for people who are unfamiliar with machine learning.
Please note that with the rapidly changing situation regarding the pandemic and Covid-19 restrictions, we will be reviewing attendance requirements and the delivery mode of this event in January to ensure that if the event does proceed with a face-to-face element, that this is consistent with regulations at that time.
10:00
→
11:00
Plenary
10:00
Introduction10m
Housekeeping
* Welcome
* Format for the event
* Reminder of where to find the pre-reading material
Speaker:
Prof.A Bevan(Queen Mary)
10:10
Data Sceince to solve real world problems - Accelex30m
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