In this paper we survey the most recent advances in supervised machine learning and highdimensional models for time series forecasting. We consider both linear and nonlinear alternatives. Among the linear methods we pay special attention to penalized regressions and ensemble of models. The...

Today, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. Machine learning describes the capacity of systems to learn from problem-specific training data to automate the process of analytical model building and solve associated tasks. Deep...

Predictive process monitoring aims at forecasting the behavior, performance, and outcomes of business processes at runtime. It helps identify problems before they occur and re-allocate resources before they are wasted. Although deep learning (DL) has yielded breakthroughs, most existing...

PART 1. INTRODUCTION AND ANALYTICS MODELS -- Retraining and Reskilling Financial Participators in the Digital Age -- Basics of Financial Data Analytics -- Predictive Analytics Techniques: Theory and Applications in Finance -- Prescriptive Analytics Techniques: Theory and Applications in Finance...