Datathon – Kaufland Airmap – Solution – Nishki
1. Business Understanding A Kaufland store is a very big thing. It has a sales floor of up to 12.000 square meters […]
1. Business Understanding A Kaufland store is a very big thing. It has a sales floor of up to 12.000 square meters […]
Catching fake news or types of propaganda is highly essential open source cause to which would like to contribute. Hence, what follows next would be our study case for the 2019 Datathon – Hack the News.
In this paper we propose the use of a combination of LSTM and EDM models to address the issue of anomaly classification and prediction in time series data. Working with sensor data for automated storage and retrieval systems for a German hypermarket chain, we show that predictors based on variance and median methods show sufficient promise in the handling of anomalies.
Techonnology and methods used: R – tidyverse, lubridate, snakecase, sp, raster, spData, sf, leaflet, mapview, ggplot2, shiny, maps, devtools, geojsonio, rgdal, leaflet.esri, leaflet.extras Python – s3fs, pandas, numpy, matplotlib, plotly 1. Business Understanding Air pollution beyond the norms is a […]