Machine learning

This chapter covers the fundamental concepts of machine learning and how they can be applied in MATLAB. First, important terms such as Artificial Intelligence, Machine Learning, and Deep Learning are introduced and defined. Different types of machine learning model (supervised, unsupervised) are introduced, as well as ways in which they can be evaluated and the potential problems that can occur when training them (overfitting, underfitting). More detail is then provided on some common types of unsupervised models (clustering and dimensionality reduction) and supervised models (classification and regression). Specific unsupervised techniques that are introduced include k-means clustering and principal components analysis (PCA). For supervised techniques, the MATLAB classification learner and regression learner apps are introduced. Finally, the concept of Deep Learning is explained as well as how to train and evaluate deep learning models in MATLAB using the deep network designer app.