Vladimir Iurcovschi & Dimitris Koulouris
Vladimir is a Mathematician, Data Scientist and Teacher. He holds a Bachelor's Degree in Mathematics and a Master's Degree in Data Science.
He has extensive working experience in Natural Language Processing, predictive modelling, data mining and a passion for deep learning to solve problems that matter. In his spare time, Vladimir enjoys teaching, travelling and collecting art.
Joining Vladimir in giving this talk is Dimitris Koulouris.
Dimitris is Full-Stack Developer at Warply. He holds a Bachelor's degree in Computer Science from Athens University of Economics and Business.
He is a passionate front-end and back-end developer with a keen interest in Artificial Intelligence. Dimitris enjoys travelling, learning new skills and hanging out with friends and family.
Processing billions of events with Python in real time
In this session will present how we approach the hot/cold processing data pipeline design pattern here at Warply. Our infrastructure can scale into processing billions of events only with pythonic open source libraries without any cloud PaaS implementation.
Hot processing constitutes of a tornado, kafka, Dask/Celery microservices and cassandra/redis, stuck. While our cold storage performs the entire machine learning model training and validation with keras and tensorflow.