PMI

Posted 4 CommentsPosted in Datathons Solutions

NFT Datathon 2022 Mentor(Alexandar Efremov)  Team(Daniel Pavlov, Martin Nenov, Aleksandar Svinarov) Technology we use: -PyCharm -CoLAb What was our approach: Our approach with the NFT sales dataset and the NFT traits type dataset:   NFT traits dataset: we made a function to generate a new trait dataset containing only the rarity score for each trait […]

Datathon – HackNews – Solution – DataExploiters

Posted 5 CommentsPosted in Datathons Solutions

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.

Hack the News Datathon Case – Propaganda Detection

Posted 3 CommentsPosted in NLP

1. Business Problem Formulation The current political landscape is shaped by extreme polarization of opinions and by the proliferation of fake news. For example, a recent study published in Science has found that rumors and fake news tend to spread six times faster than truthful information. This situation both damages the reputation of respectable news outlets and […]

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

Posted 2 CommentsPosted in Prediction systems

Kaufland-Case 1. Business Understanding Industrial vibration analysis is a measurement tool used to identify, predict, and prevent failures. Implementing vibration analysis on the machines will improve the reliability of the machines and lead to better machine efficiency and reduced down time eliminating mechanical or electrical failures. Vibration analysis are used to identify faults in machinery, plan machinery […]

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

Posted 6 CommentsPosted in Prediction systems

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 !