Welcome to  DIHUB Platform

Students designed and impelemented a Microsoft 365 solution for a multi-site restaurant company.

Hands-on training and instructions were also provided for the employees.

Chatbot solution was developed for an e-commerce company that sells various party, festival and bakery related products.

Students also analyzed and developed few modifications for the company's digital marketing.

Website redesign project where demosite was hosted and developed on Google Cloud Platform.

Students also tested cloud based Calendly service for the companys appointment scheduling needs.

Developing and improving online communication and file handling capabilities off a SME speciliazed on workforce and recruitment business.

Students also designed basic structure of an A.I. based chatbot for the company.

Students created and analyzed various use case concepts for a company that creates innovative service robot solutions.

Chosen topics were based on utilizing robotics in education, learning and other day-to-day activities at school.

Using AI trained drones to monitor crops can dramatically increase farm yields while minimizing the labor, time, and cost of traversing the field on foot or by vehicle, as well as having a drone take pictures over the crops.

Building a chatbot for answering questions on Finland and the World Expo at Dubai using the tools in the IBM Cloud.
The task of the business information technology students was to design the architecture of the implementation, implement it and to use test automation tools to monitor the quality of the produced chatbot.

Projects goal was set to optimize wind farm turbines' performance by 8-10%, by optimizing the guidance based on the meteorological forecast and the accumulated databases for the last 10 years. A virtual machine in the cloud processed Big Data creating a model for each day of the year.

Creating a machine learning model to identify topics based on WhatsApp messages using NLP (Natural Language Processing) algorithms.
This project aimed to develop a library named WhatsAppNLP which combines and as a final product simplifies the process of training machine learning models, its application and application of analysis methods chat log entries.

The aim of this project is to develop and understand models for the prediction of three subjective attributes of images - memory, curiosity and positive sentiment, and to compare the effectiveness of simultaneous learning tasks with the effectiveness of learning a single task.
The models developed in the project are based on deep convolutional neural networks.

The project goes through the basics of traditional and modern algorithms and demonstrates where traditional techniques fail at the task of key vehicle characteristic detection.
Real car images are used to demonstrate the workings of several models: for license plate detection, brand detection, and color detection.