In this lecture, the basis of machine learning and data mining will be explained. Then, the most typical problems where machine learning is applied will be presented: classification, clustering, regression and anomaly detection. For those problems, some techniques that can be applied will be presented and briefly explained: decision trees, support machine vectors, k-NN, k-means and neural networks.