Career Satisfaction of programmers in Eastern Europe

The goal of this paper is to learn how to apply apriori association rules algorithm with R. In this paper we will analyze a random dataset generated with the help of the website: https://www.dunnhumby.com/. It contains 2000 different supermarket baskets/transactions in two different periods of time, with other additional information. For the purposes of this paper, the columns PROD_CODE (character, with the format: PRD0+6numbers) and BASKET_ID (number with 15 digits) will be selected.

The goal of this paper is to apply dimensionality reduction techniques to the selected data. To this end, I chose several data from Eurostat-database, in order to discover if it is possible to reduce features without lossing quality of the following dataset: trade in the European Union (28 countries) during 2018 Last but not least, in the extensions we will see how dimensionality reduction through image compression can be applied

The goal of this paper is to analyze the evidence of clustering based on the selected data. To this end, I chose several data from Eurostat-database, in order to find out if there are clusters in term of trade in the European Union (28 countries).

Original shiny dashboard page: https://lajobu.shinyapps.io/Covid-19_project/

Machine Learning classification methods