Machine Learning is becoming one of the most popular technologies in the world bringing its capabilities to people’s work and lives. The ideas and prospects of Machine Learning we realize in Natural Language fields. We are going to show here how do we work with Machine Learning algorithms, which techniques we utilize, what kind of tasks we solve and tell you about our project. Let’s go!
Here you can check the more detailed article in which we described how to build a semantic search pipeline using open-source components and a little bit of coding (based on our project OneBar).
Kenny R. Lienhard
CTO, Medignition Inc
We wanted to implement a new education platform that offered online courses in finance. The scope focused on the implementation of multiple user interfaces. UpsilonIT used React, GraphQL, and GatsbyJS. UpsilonIT had strong coding skills. The app had a clean codebase and complied with all specifications. They complied with our requirements for the UI. We communicated daily via Slack.
CTO, Civic Connect
Upsilon’s work was always on time and met all customer expectations. Their team had an ease of communication but what was the most impressive about them is the integrity and work ethic of each member. We had a business manager, a lead architect, and a mix of senior and regular engineers. The workflow was extremely effective - the teams had a regular cadence for communication.
Creative Consultant, Etage Group
We needed help with mobile app development, data analytics, and beacon installation to be able to collect, store, and analyze our customer data. The finished application met the requirements perfectly, with the team finding an excellent solution to collect, analyze, and store customer data. They were highly professional throughout the work, always making themselves available, and responding well to any changes.
Director of Engineering, Carggo
Upsilon provided front- and backend development for an online logistics platform. The team designed and launched a business intelligence platform and ensured scalability according to customer requirements. We were most impressed by the technical background of the specialists, their meaningful approach to task accomplishment, and aspiration to deliver the results in due time. We’re also pleased with how fast the team started the development.