PyData is a specialist event within the framework of PyCon at which all interested parties and experts exchange information on data science. The event took place from October 8th to 10th in Berlin and we from ella were there as well.
“We attended the event to further educate ourselves in the field of data analysis and to get a current impression of the industry,” says Nasrin Saef, Machine Learning Engineer at ella. “And I can only say that it was worth it!
Dr. Rasmus Krempel, Senior Data Scientist at ella, also agrees: “The conference gives a good overview of the trends in data processing and visualization with Python. The hands-on experience that will be exchanged here cannot be read!
In over 100 workshops, lectures and tutorials on data science, the participants of the event were able to expand their knowledge, exchange ideas and share their own expertise. Among other things, our ella team participated in the lecture “Gaussian Progress” on the complexity of algorithms or in the workshop “Are you sure about that?! Uncertain Quantification in AI” on Deep Learning from AI to get an even more specific insight into the principle of algorithms, machine learning and other AI topics.
“I particularly enjoyed the Data Engineering workshops,” says Dr. Mario Deng, Head of Data Analytics at ella. “There was always a very intensive exchange in the area of data and IT infrastructure”.
Andreas Funke, Machine Learning Engineer at ella: “We also learned a lot from this event in the area of Machine Learning. The expertise there on AI and data is enormous.”
PyData has been the event of the IT and AI industry for years and takes place several times a year at various locations worldwide. The focus of the event is always on programming and data science.
“All in all, I am very enthusiastic about the expertise there and the very exciting topics,” says Deng. Data analysis is an essential part of the ella-KI. The aim is for the AI to receive consumer, market and trend data in addition to the enormous book inventory, so that it can automatically produce currently relevant text content.