World Scientific just published the work “Machine Learning — A Journey to Deep Learning”, written by INESC-ID researcher Andreas Wichert and  his PhD student Luís Sá-Couto.

This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives — the statistical perspective, the artificial neural network perspective and the deep learning methodology.

The useful reference text represents a solid foundation in machine learning and should prepare readers to apply and understand machine learning algorithms as well as to invent new machine learning methods. It tells a story outgoing from a perceptron to deep learning highlighted with concrete examples, including exercises and answers for the students.

The book is available here.

About the authors:

Andreas Wichert studied computer science at the University of Saarland, where he graduated in 1993. Afterwards, he became a PhD student at the Department of Neural Information Processing, University of Ulm. Since 2006 he is Assistant Professor at Department of Computer Science and Engineering, University of Lisbon where he is as well lecturing about machine learning and quantum computation. His research focuses on neuronal networks, cognitive systems and quantum computation.

Luis Sa-Couto studied computer science at the Department of Computer Science and Engineering, University of Lisbon, where he graduated in 2018. Since then he is a PhD student under the supervision of Prof Andreas Wichert with the topic Extending Deep Learning Applicability Through Attention-inspired Networks for Object Recognition. He lectured practical classes in AI and machine learning.