Author: alex-efremov

Posted junior, stephen, zenpanik, alex-efremov, pepe, tomislavk, liad, preslav, tony, laura, mladensavov, anenov, metodinikolov, drceenish, leomrsic, boryana, mcneto, jjagusch, drsubhabahapal, sist, jans, gkmitov, metodinikolov, gloria, quintshekhar1 CommentPosted in GD2018 Mentors, MentorsGD2018 Mentors, Mentors

Datathon NSI Mentors’ Guidelines – Economic Time Series Prediction

In this article the mentors give some preliminary guidelines, advice and suggestions to the participants for the case. Every mentor should write […]

Posted junior, zenpanik, alex-efremov, pepe, tomislavk, liad, preslav, tony, laura, mladensavov, anenov, metodinikolov, drceenish, leomrsic, boryana, mcneto, jjagusch, drsubhabahapal, sist, jans, gkmitov, metodinikolov, gloria, quintshekharLeave a commentPosted in GD2018 Mentors, MentorsGD2018 Mentors, Mentors

Datathon Telenor Mentors’ Guidelines – On TelCo predictions

In this article the mentors give some preliminary guidelines, advice and suggestions to the participants for the case. Every mentor should write […]

Posted junior, zenpanik, alex-efremov, pepe, tomislavk, liad, preslav, tony, laura, mladensavov, anenov, metodinikolov, drceenish, leomrsic, boryana, mcneto, jjagusch, drsubhabahapal, sist, jans, gkmitov, metodinikolov, gloria, quintshekharLeave a commentPosted in GD2018 Mentors, MentorsGD2018 Mentors, Mentors

Datathon Sofia Air Mentors’ Guidelines – On IOT Prediction

In this article the mentors give some preliminary guidelines, advice and suggestions to the participants for the case. Every mentor should write […]

Posted junior, zenpanik, alex-efremov, pepe, tomislavk, liad, preslav, tony, laura, mladensavov, anenov, metodinikolov, drceenish, leomrsic, boryana, mcneto, jjagusch, drsubhabahapal, sist, jans, gkmitov, metodinikolov, gloria, quintshekharLeave a commentPosted in GD2018 Mentors, MentorsGD2018 Mentors, Mentors

Datathon Kaufland Mentors’ Guidelines – On Predictive Maintenance

In this article, the mentors give some preliminary guidelines, advice, and suggestions to the participants for the case. Every mentor should write […]

Posted junior, zenpanik, alex-efremov, pepe, tomislavk, liad, preslav, tony, laura, mladensavov, anenov, metodinikolov, drceenish, leomrsic, boryana, mcneto, jjagusch, drsubhabahapal, sist, jans, gkmitov, metodinikolov, gloria, quintshekharLeave a commentPosted in GD2018 Mentors, MentorsGD2018 Mentors, Mentors

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 […]

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ACADEMIA DATATHON CASE: THE A.I. CRYPTO TRADER

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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.