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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.
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.
Jeremy Howard (born 13 November 1973) is an Australian data scientist, entrepreneur, and educator. [1] He is the co-founder of fast.ai, where he teaches introductory courses, [2] develops software, and conducts research in the area of deep learning. Previously he founded and led Fastmail, Optimal Decisions Group, and Enlitic.
Data covering the nonlinear relationships observed in a servo-amplifier circuit. Levels of various components as a function of other components are given. 167 Text Regression 1993 [160] [161] K. Ullrich UJIIndoorLoc-Mag Dataset Indoor localization database to test indoor positioning systems. Data is magnetic field based. Train and test splits ...
The Global Energy Forecasting Competition (GEFCom) is a competition conducted by a team led by Dr. Tao Hong that invites submissions around the world for forecasting energy demand. [1] GEFCom was first held in 2012 on Kaggle , [ 2 ] and the second GEFCom was held in 2014 on CrowdANALYTIX.
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A data structure known as a hash table.. In computer science, a data structure is a data organization and storage format that is usually chosen for efficient access to data. [1] [2] [3] More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data, [4] i.e., it is an algebraic structure about data.
DVC is a free and open-source, platform-agnostic version system for data, machine learning models, and experiments. [1] It is designed to make ML models shareable, experiments reproducible, [2] and to track versions of models, data, and pipelines. [3] [4] [5] DVC works on top of Git repositories [6] and cloud storage. [7]