Let’s get back to the basics! Join us in a 1-hour long coding and learning session, organized in the context of DEVit week. DEVit is among the top web developer conferences in Europe and has become known for its top speaking talent, a mixture of world-class and world-renowned developers, highly specialized technology niches and developers who are on the edge of technology frontiers.
In this meetup, we will provide a smooth introduction to machine learning and deep learning for those who are now getting into this field and missed our previous meetups. So, this is your opportunity 😉 More specifically, we will briefly review the most important Python libraries that are used for machine learning and then introduce the superstar: keras. Keras is a well known deep learning library for Python that significantly simplifies the process of developing and training deep learning models. Keras provides support for all the major deep learning paradigms, ranging for simple Multilayer Perceptrons (MLPs) and Convolutional Neural Networks (CNNs) to Recurrent Neural Networks (RNNs) and Generative Adversarial Networks (GANs). This is a hands-on only session (no slides and boring stuff, we will use the blackboard for explaining more complicated concepts), so get your laptop with you and follow us as we are going through several examples demonstrating how Python can be used for machine learning.
P.S. Please be sure to learn Python using Machine Learning before attending this meetup!
– 19:45: Welcome and Introductions, Doropoulos Stavros, Meetup Organizer
– 19:55: Pretend you know Machine Learning using Python, Nikolaos Passalis
– 20:45: Networking and socializing
Bio: Nikolaos Passalis is a postdoctoral researcher at the Faculty of Information Technology and Communication Sciences, Tampere University, Finland. He received the B.Sc. in Informatics in 2013, the M.Sc. in Information Systems in 2015 and the Ph.D. degree in Informatics in 2018, from the Aristotle University of Thessaloniki, Greece. He has (co-)authored more than 45 papers published in international journals and conference proceedings. His research interests include deep learning, computational intelligence and information retrieval.
What to bring
Participants are encouraged to bring their laptops with numpy, scikit, keras and tensorflow installed to actively participate in the session.