Analytics and Big Data Engineering

Deep Learning

Ludwig Krippahl (DI/FCT NOVA)

Ludwig Krippahl teaches at the Computer Science department of FCT/NOVA, mostly courses on machine learning and bioinformatics. With a background in artificial intelligence and biochemistry, his main research interests are in the application of AI to bioinformatics.

Abstract: Even though artificial neural networks have been around since the beginning of machine learning – Rosenblatt proposed the original perceptron in 1954 – only in recent years has the potential of these models begun to be realized. This lecture is a brief introduction to deep learning, covering developments leading to the current explosion in research and applications, the versatility of deep neural networks, and how these models can be applied to different types of machine learning problems, such as unsupervised, supervised and reinforcement learning.

Churn Predictive Modelling

Sara Machado (MSc Student MAEBD/FCT NOVA)

I have a degree in Mathematics from the Faculty of Science and Technology of the NOVA University of Lisbon. I am currently attending the 2nd year of the Master in Analysis and Big Data Engineering.

Abstract: Customer churn prediction in the business world is nowadays a fundamental business management tool. In particular, churn modeling is typically based on past customer consumption history and is used to classify current customers by their probability of churn. During this talk I will talk about Machine Learning models, such as logistic regression, that can be used to predict this type of behavior.

Artificial Intelligence in Business Automation

José Cruz (BNP Paribas)

I'm head of the Analytics Consulting Data Lab at BNP Paribas, Lisbon. I lead a team of Data Scientists dedicated to solve business problems with data, models and computers. I have a degree in Computer Engineering from IST and a PhD in Computational Biology from U. Strasbourg. I spent most of the last 25 years designing, developing and managing all kinds of software projects for big and small organizations in commercial, academic and research institutions. I enjoy learning and to be surrounded by brilliant people.

Abstract: The automation of productive tasks has been a common hallmark in most economical revolutions throughout history. Today, Artificial Intelligence is a major driving force of automation in business and will probably contribute to the economic revolution started with the digital era. In this lecture we will present a practical case of automation of a business process in BNP Paribas. From the problem definition, to the value generation phase, we will show how we applied modern AI and Machine Learning techniques in a real life project. Finally, we will show (again) why applied mathematicians is an increasingly demanded profile in modern industry.