Demystifying: machine learning
Demystifying: machine learning
The event will include an introduction to machine learning, covering the basic knowledge of supervised, semi-supervised and unsupervised learning. Then, we will move to a discussion of convolutional neural networks (CNNs) and the concepts that are used to build them. These concepts will be accompanied by practical implementations of the algorithms presented.
Examples will be provided to the attendees in a way that will allow them to run the code in their own workspace. Experimentation on the provided code guided by the instructors will allow the attendees to understand how different techniques are combined to solve a problem. We will discuss modifications that will allow the machine learning techniques studied to present better results and/or be applied to different use cases. Instructors will also share some pitfalls and mistakes made when applying machine learning, and how they overcame these.
The example code will be written in Python, and the attendees will run their code using Google Collab.
Mills, Ben
05f1886e-96ef-420f-b856-4115f4ab36d0
Grant-Jacob, James A.
c5d144d8-3c43-4195-8e80-edd96bfda91b
Zervas, Michalis
1840a474-dd50-4a55-ab74-6f086aa3f701
28 July 2024
Mills, Ben
05f1886e-96ef-420f-b856-4115f4ab36d0
Grant-Jacob, James A.
c5d144d8-3c43-4195-8e80-edd96bfda91b
Zervas, Michalis
1840a474-dd50-4a55-ab74-6f086aa3f701
Mills, Ben, Grant-Jacob, James A. and Zervas, Michalis
(2024)
Demystifying: machine learning.
Optica Advanced Photonics Congress 2024: 2024 Demystifying Program, French Quebec, Quebec, Canada.
28 Jul - 01 Aug 2024.
Record type:
Conference or Workshop Item
(Other)
Abstract
The event will include an introduction to machine learning, covering the basic knowledge of supervised, semi-supervised and unsupervised learning. Then, we will move to a discussion of convolutional neural networks (CNNs) and the concepts that are used to build them. These concepts will be accompanied by practical implementations of the algorithms presented.
Examples will be provided to the attendees in a way that will allow them to run the code in their own workspace. Experimentation on the provided code guided by the instructors will allow the attendees to understand how different techniques are combined to solve a problem. We will discuss modifications that will allow the machine learning techniques studied to present better results and/or be applied to different use cases. Instructors will also share some pitfalls and mistakes made when applying machine learning, and how they overcame these.
The example code will be written in Python, and the attendees will run their code using Google Collab.
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More information
Published date: 28 July 2024
Venue - Dates:
Optica Advanced Photonics Congress 2024: 2024 Demystifying Program, French Quebec, Quebec, Canada, 2024-07-28 - 2024-08-01
Identifiers
Local EPrints ID: 493472
URI: http://eprints.soton.ac.uk/id/eprint/493472
PURE UUID: a7fb201e-f648-44a2-8eb3-01131dd75255
Catalogue record
Date deposited: 03 Sep 2024 16:48
Last modified: 04 Sep 2024 01:43
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Contributors
Author:
Ben Mills
Author:
James A. Grant-Jacob
Author:
Michalis Zervas
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