In this chapter, we present the main classic machine learning algorithms. A large part of the chapter is devoted to supervised learning algorithms for classification and regression, including nearest-neighbor methods, linear and logistic regressions, support vector machines and tree-based algorithms. We also describe the problem of overfitting as well as strategies to overcome it. We finally provide a brief overview of unsupervised learning methods, namely for clustering and dimensionality reduction. The chapter does not cover neural networks and deep learning.