Datathon Ontotext Mentors’ Guidelines – Text Mining Classification
In this article the mentors give some preliminary guidelines, advice and suggestions to the participants for the case. Every mentor should write […]
In this article the mentors give some preliminary guidelines, advice and suggestions to the participants for the case. Every mentor should write […]
Data preparation The first step in our analysis was to see if there are any observations missing. Some dates were not even […]
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In an attempt to make a case which is to be somewhat universally understandable by various types of students, the case is financial time-series prediction, while making it more engaging with the hot topic of cryptocurrencies. The case integrates knowledge from various sources – Crypto Currencies, Quantitative Finance and Machine learning. At the same time, the case is stratified as the teams solving it could complete various levels – as far as they could solve it.
Team members: Ana Popova, @anie Izabella Taskova, @ izabellataskova Kamelia Kosekova, @kameliak Kameliya Lokmadzhieva, @kameliyalokmadzhieva Nikolay Bojurin, @nikolay Mentors: @boryana @alex-efremov @pepe […]
Techonnology and methods used: R – plyr, dplyr, tidyverse, stringr, data.table, geohash, ggmap, maps, robustbase, geosphere, pracma, Hmisc, ggplot2, tidyquant, reshape2, pastecs Python […]