Tag: datathon

Posted ahmed, shehel, blackhoodie Mentors: preslav, laura, vsenderov, giovanni, alberto5 CommentsPosted in Datathons SolutionsDatathons Solutions

Datathon – HackNews – Solution – DataExploiters

This article describes our submission for the Hack the News Datathon 2019 which focuses on Task 2, Propaganda sentence classification. It outlines our exploratory data analysis, methodology and future work. Our work revolves around the BERT model as we believe it offers an excellent language model that’s also good at attending to context which is an important aspect of propaganda detection.

Posted dobrina, krisispasova, dobrina, ogi1, pacopacov, krisispasova, pacopacov, michael-opitsch, penchodobrev, sist Mentors: penchodobrev, michael-opitsch2 CommentsPosted in Prediction systemsPrediction systems

Datathon Kaufland Solution – Predictive Maintenance Based on Sensor Data for Forklifts

Kaufland-Case 1. Business Understanding Industrial vibration analysis is a measurement tool used to identify, predict, and prevent failures. Implementing vibration analysis on […]

Posted omki, abhinandanarya, junaid, apoorvakesarwani Mentors: drsubhabahapal6 CommentsPosted in Prediction systemsPrediction systems

Datathon NSI Solution – The curious case of ‘Household Budget Survey(HBS)’

The National Statistical Institute of Bulgaria (NSI) conducts annually a Household Budget Survey (HBS) with an objective to get reliable and scientifically founded data on the income, expenditure, consumption and other elements of the living standard of the population as well as changes, which have occurred during the years. NSI is considering a change in the periodicity of the Household Budget Survey from yearly to once on every five years,In order to optimize the cost of carrying out the survey. Hence We are creating a model which will predict household expenditure for the next four years using linear regression model and time series. The algorithms that we will be taking help from are linear regression model & Autoregressive integrated moving average(ARIMA). So lets not waste any time and move on with it !