Datathon Host Guidelines
Rules Background Specific rules for hosts Each local group has general guidelines from Data Science Society to manage the Datathon to fit […]
Crypto predictions #Fake it
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Forecast the price of cryptocurrency
Dear jury, We are students from Faculty of Economics and Social Sciences, University of Plovdiv Paisii Hilendarski. As we are first year […]
The next Digital Marketing Intern to join the DSS Legion of Super-Heroes
Data Science Society is an international digital community which has been building a strong core of members digitally around a body of […]
Team Chinchillas, Telenor SNA case
Business Understanding Telenor wants to identify Social Network leaders from a list of A and B nodes, their connection counts and connection […]
404 Telenor Social Media Not Found
Social networks are characterized by the links between the nodes. We employed six different link analysis algorithms to rank the nodes in the network by their importance. For the task of leader detection, the best link analysis algorithm proved to be the vanilla PageRank. Out of the top 2000 nodes, 1725 are leaders, achieving a precision of 0.8625 and a recall ot 0.8792.
We also explored an alternative solution based on embeddings. We trained a Skipgram model where we set the context of a given node to its neighbourhood. To avoid the assumption for word order made by the model we repeated and reshuffled longer neighbourhoods. These embeddings were then used to train a softmax classifier, achieving a macro-f1 score of 0.6667.
We futher provide a visualization tool which can be used to explore the graph manually.
The SAP Case – Analyze Sales
Have you ever wondered if retailers actually make more money from price discounts? Or what is the impact of promotions in Amazon on the sales in Walmart? The SAP case is about price optimization and promotional effectiveness.
The Kaufland Case – Recognize the Product
On 22.01.2018 Amazon opened Amazon Go – their first ever physical store without cashiers and checkout lines – customers just grab the products from the shelves and go. AI algorithms detect what product you have grabbed.
Kaufland offers the unique opportunity to work with their internal data on a similar problem – developing a computer vision algorithm that detects which is the fruit or vegetable scanned.
ACES solution to article recommender engine case – provided by NetInfo
Authors The ACES team that worked on the solution is listed in alphabetical order: Atanas Blagoev ([email protected]) Atanas Panayotov([email protected]) Emil Gyorev ([email protected]) […]
Datathon – Kaufland Airmap – Solution – Phoenix
Overview Our approach to the problem is as follow: Data Augmentation – in the data augmentation phase we are creating synthetic images […]
Datathon – Sofia Air 2.0 – Solution – Predikt (Sofia Air 2.0) Github: scopyro
GitHub Accounts: KarimEid1, Marcel344, scopyro , @boudy87
Air pollution is quite a topic today. The municipality is investing a lot of effort and resources in order to measure the exact values of the gases and particulate matter in the air in order to identify its quality.
This is the next step towards the completion of a story and holistic view over the data-driven and explained the social topic of unveiling the secrets behind the information about Sofia Air Quality.
This research differentiates the main sources of pollution in Sofia and tries to predict what are the growing rate of this pollution in order to rise awareness against this danger and visualize, in numbers, its growth rate.