Machine learning

Machine learning · 24. February 2019
Here we explore the pros and cons of some the most popular classical machine learning algorithms for supervised learning. To recap, this is a learning situation where we are given some labelled data and the model must predict the value or class of a new datapoint using a hypothesis function that it has learned from studying the provided examples. By ‘classical’ machine leaning algorithms I mean anything that is not a neural network. We will cover the advantages and disadvantages of various...
Machine learning · 17. February 2019
We explore what it means for a machine learning model to generalize well. These concepts are important to keep in mind when thinking about all sorts of supervised machine learning problems.
Machine learning · 10. February 2019
Where we take a look at some of the common metrics for evaluating the success of classification models