Introduction

Machine intelligence is “a branch of artificial intelligence that focuses on building applications that learn from data and improve their accuracy over time without being programmed to do so” [1]. This is an important and rapidly developing technique that has applications in fields as diverse as aerospace and biomedical engineering. In biomedical engineering, ML is used for an expanding range of applications including medical imaging processing, for instance to extract, analyze and categorize brain tumours from MR images [2], diagnosing heart disease from phonocardiograms [2] and motion planning of upper limb exoskeletons [3].  

Workshop and Submission

Tina and Lucy, Engineering Science students majoring in Machine Intelligence, have prepared this 1-hour workshop with the goal of introducing you to machine learning concepts. They introduce machine learning categories, go over the general workflow, including important considerations in setting up a dataset, and then work through convolutional and recurrent neural networks. If you are interested, there are many resources that go into more detail and work through implementation. Please see the Further Resources section.

To check your understanding, please complete this form after you have watched the workshop. ​

ML MODULE FORM

Further Resources

The following provides more information and tutorials on Machine Learning:

• Computer Education: Machine Learning: Suggested by a friendly team, this article by HP explains what Artificial Intelligence and Machine Learning is and provides further resources. Good to read when covering the basics!
• What is Machine Learning?: IBM's article with embedded links to additional topics
• Machine Learning Tutorials: By IBM with step-by-step instructions and sample code for specific tasks
• Learn Machine Learning: Tutorials using the prerequisite of basic Python by Tutorials Point

There are also many free courses on Coursera of various levels and lengths. The following are a selection of these courses:

• Fundamentals of Machine Learning for Healthcare: Basic introductory course offered by Stanford University
• Introduction to Machine Learning: Intermediate level course providing a foundational understanding of machine learning models offered by Duke University
• Predictive Modeling and Machine Learning with MATLAB: Intermediate level course utilizing Matlab offered by MathWorks
• Machine Learning: Broad introduction course that delves into some of the mathematics and theory behind ML and its applications, offered by Stanford University
• IBM Machine Learning Professional Certificate: Intermediate level resource to develop working skills in main areas of Machine Learning

References

[1] IBM Cloud Education, ‘What is Machine Learning,’ 2020. [Online]. Available:  https://www.ibm.com/cloud/learn/machine-learning . [Accessed: 11-Jan-2021]
[2] Park, C., Took, C.C. & Seong, JK. Machine learning in biomedical engineering. Biomed. Eng. Lett. 8, 1–3 (2018). https://doi.org/10.1007/s13534-018-0058-3
[3] C. Lauretti et al., “Learning by Demonstration for Motion Planning of Upper-Limb Exoskeletons,” Frontiers in Neurorobotics, vol. 12, p. , Feb. 2018.