Team name: Cheetahs Case: Telelink (iGEM) Provider: IBM Business Understanding The task for the Telelink case is to obtain the complete set of genome traces found in a single food sample and ALL organisms that should not be found in the food sample. The business needs a solution to this DNA Sequence identification case for improved […]
Case Kaufland¶ 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 […]
We developed workflow utilizing Blast and Centrifuge toolkits, that is able to provide precise metagenomics information about food composition, from comparing DNA reads with reference genomes of various species. Our workflow is optimized to work on Google Cloud instance (Compute Engine) with 24 CPUs and 200 GB of RAM.
This paper presents a DNN-based approach to learn entities relations from distant-labeled free text. The proposed approach presents task-specific data cleaning, which despite effective in removing textual noise is preserving semantics necessary for the training process. The cleaned-up dataset is then used to build a number of bLSTM attention-based DNN models, hyper-tuned using recall as an optimization objective. The resulting models are then joined into an ensemble that deliver our best result
About¶Entry: Data Science society Datathlon 2018 Case: SAP Case Dataset: available here Authors: Hristo Piyankov (firstname.lastname@example.org) Notes: not all caclulations and graphs are carried out in python, due to time constraints Business understanding¶ Goal of the study is to udnerstand drivers behind sales up-lift with relation to the company’s own pricing strategies, promostions and competitors.’Identify […]