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Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
Anthony John Goldbloom (born 21 June 1983) is the founder and former CEO of Kaggle, a data science competition platform which has used predictive modelling competitions to solve data problems for companies, such as NASA, Wikipedia, [1] Ford and Deloitte. Kaggle has operated across a range of fields, including mapping dark matter [2] and HIV ...
Howard first became involved with Kaggle, founded in April 2010, [9] after becoming the globally top-ranked participant in data science competitions in both 2010 and 2011. The competitions that Howard won involved tourism forecasting [10] and predicting the success of grant applications. [11] Howard then became the President and Chief Scientist ...
Wikipedia abstracts aligned with Wikidata entities Alignment of Wikidata triples with Wikipedia abstracts 11M aligned triples JSON and NIF : NLP, Relation Extraction 2018 [109] H. Elsahar et al. General Language Understanding Evaluation (GLUE) Benchmark of nine tasks Various ~1M sentences and sentence pairs NLU 2018 [110] [111] [112] Wang et al.
Examples of data science competition platforms include Bitgrit, [3] Correlation One, Kaggle, InnoCentive, Microprediction, [4] AIcrowd, [5] and Alibaba Tianchi. [6] Alibaba's competition platform was used in KDD 2017.
The competition was hosted on Kaggle, a service that runs data science competitions. It included two tracks: a hierarchical load forecasting track and a wind power forecasting track; both opened to contestants in September 2012.
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It used real-life data from Walmart and was conducted on Kaggle's Platform. It offered substantial prizes totaling US$100,000 to the winners. The data was provided by Walmart and consisted of around 42,000 hierarchical daily time series, starting at the level of SKUs and ending with the total demand of some large geographical area.