Communication between disciplines
Engaging with another discipline, such as at the interface between computer science and biosciences, is largely a challenge of communication. Building AI models currently needs a good level of programming …
Course: Experimental Design for Machine Learning
How much should we trust AI models?
It is important to remember that AI is not magic. Most of AI is a form of advanced pattern recognition. By training through example data – images for example – …
Synthetic data and generative AI
In the video we thought about how we can use tools like 3D modelling, image generation or style transfer – including generative AI approaches – to help expand datasets. Why …
Tasks in machine learning
To expand on the previous video, these are the types of tasks that we often encounter when using machine learning for plant phenotyping. 1. Classification Classification involves classifying, or labelling, …
Introduction to Week 5
Welcome to Week 5 of the course, the final week. In this final week we will begin in the first activity by giving some advice on the following topics: software …
Week 5 review
Congratulations on completing the Week 5 of the course, the final week. Before we wrap up the course, here’s a quick recap of the main topics we covered in the …
Introduction to Week 4
Welcome to Week 4 of the course. By now, we’ve been touched on all the key steps needed to produce a working machine learning model, and the data it is …
Week 4 Review
Well done on completing Week 4 of this course. In the videos we talked about various different aspects of the outputs and outcomes of machine learning and deep learning models …
Introduction to Week 3
Welcome to Week 3 of the course. In the first two weeks we were mainly concerned with data acquisition and getting the data in suitable shape for use in machine …
Introduction to week 2
Welcome to week 2 of the course. Last week we focused on data acquisition and annotation, the experimental phase of the project. This week we will look in more detail …
Week 3 review
Congratulations on completing Week 3 of the course. We hope it has given you some pointers on what to think about when selecting and training a machine learning model using …
Transfer learning
What is transfer learning? Transfer learning refers to the idea that we can get an AI model to gain useful information from one domain, and transfer that knowledge across to …
Week 2 review
That’s the end of Week 2 of the course. We hope that it has given you some useful ideas as to the best ways to organise and maximise the use …
Week 1 review
Well done on completing Week 1 of the course. We hope you have found it useful so far and it has given you some ideas of what to think about …
What we will cover in the course
Week by week The main topics we will cover during this five-week course are as follows: Week 1 – data collection and annotation: Choosing the problem – what type of …