human / unsupervised

Go to Jupyter Notebook

Logistic Regression is one of the most well known regression algorithms in the world and is used extensively in classification problems (ie labelling inputs as belonging to a particular class.) Similar principles to Linear regression apply here and we go through how we implement cost functions and gradient descent for logistic regression problems. We also explore some new concepts. Including optimisation algorithms and some practical Matlab code implementing gradient descent, how to recognise overfitting and underfitting, and regularisation.