What makes a good feature? You can use your knowledge of the domain to select important features, or you can combine features to make new features (feature engineering). This video …
How might we use data for machine learning? This video gives an introduction to features and how the choice of useful features will vary depending on the context.
What is semi-supervised learning? As the name suggests, it sits somewhere between supervised and unsupervised learning, often when you have a large amount of unlabelled data, and a small amount …
What is supervised learning? If your data has a known output label or target, which you want to predict based on a set of inputs, it is a supervised learning …
What is unsupervised learning? If you have a dataset which has no specific output or target feature, you may still want to discover more about the structure of the data. …
What kinds of data can we get from images? Image data can be the pixels themselves, but more commonly we use specific measurements or features directly extracted from the image. …
Welcome to the course: Machine Learning for Image Data. The course is designed to take around four hours a week over five weeks to complete. It is aimed at bioscience …
Before we try some simple neural network and deep learning examples we will introduce some related software tools, Python notebooks (specifically Jupyter) and Colab. Both run in a web browser …
This article provides a quick overview of the Python plotting tool Matplotlib. An important part of any work involving the use of quantitative data is visualisation of that data and …
What is Pandas and what do we need it for? To use the machine learning tools in scikit-learn you need to provide it with training data in a particular format, …
Scikit-learn is a popular Python package that can be used to perform a range of machine learning tasks. It comes ready-installed if you have an Anaconda distribution of Python, but …
The main topics we will cover during this five-week course are as follows: Week 1 – introduction to machine learning: Introduction to machine learning for image data Software tools Key …
In this article we will demonstrate how to perform the two methods of dimensionality reduction we discussed previously, PCA and and tSNE. Both examples use scikit-learn and its built in …
As we saw in Week 1, K-means is a simple unsupervised learning clustering technique. In this article we briefly review how it works, and give an example of using it …