by Sergi Sergiev | Mar 30, 2020 | Blog
Why SuperSet? Superset is a data exploration platform designed to be visual, intuitive and interactive, the main objective is to slice, dice and visualize data easily. It is open-source BI platform which can be deployed on every virtual server with no usage costs. Some of the main advantages are: it is maintained by Apache foundation and supported by AirBnB Many visualization and ability to edit the code Support geolocations and uses mapbox Able to cache data for dashboards visualizations Admin panel available with very detailed settings Able to access many SQL and NoSQL databases Easy and friendly user interface According to GitHub repo, Superset is currently being used by Airbnb, Twitter, GfK Data Lab, Yahoo!, Udemy and many others. We at ShopUp decided to give a try of that great platform and noticed that as products driven by the community, sometimes there is missing documentation. We have met some difficulties in setting up the platform on EC2...
by Sergi Sergiev | Aug 14, 2019 | Blog
A Retail Case study about implementing recommender systems developed during the Summer School of Research Methods In summer 2019, some of the ShopUp team took part in the Summer School of Research Methods. The 7-day event was organized by several members of Data Science Society and academia representative from Sofia University, UNWE and Technical University Sofia. There were more than 10 lecturers and about 30 participants from different companies, organizations and universities. Among them were experts, researchers, PhD candidates and masters students. Each day the program started with presentations or workshops followed by allocated time for a Capstone project (a project which aims to capture what we’ve learnt). The workshops combined practice and theory in the area of maths, statistics, neural network, reinforcement learning and etc. The Capstone project was mandatory for each participant and there were three different cases to select from. We at ShopUp decided to open-source this project work and share it with the community. The code we created is...
