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The Makridakis Competitions (also known as the M Competitions or M-Competitions) are a series of open competitions to evaluate and compare the accuracy of different time series forecasting methods. They are organized by teams led by forecasting researcher Spyros Makridakis and were first held in 1982. [1] [2] [3] [4]
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.
TimeIQ (now known as FAME Java Toolkit) beta 1 was released. FAME created an object-oriented Java programming interface. 2001: FAME 9.0 increased the FAME database size limit from 2 GB to 64 GB. 2002: FAME 9.0 for Windows released; 2003: FAME 9.0 ported to Linux; 2004: access Point (now known as FAME Web Access) with connection pooling released
A framework for discrete-event simulation in Java, supporting hybrid event/process models and providing animation in 2D and 3D. gem5: C++: Application August 8, 2024 BSD: The gem5 simulator is a modular platform for computer-system architecture research, encompassing system-level architecture as well as processor microarchitecture. [17] JaamSim ...
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.
Sentiment analysis, summarization, classification 2006 [83] [84] J. Schler et al. Social Structure of Facebook Networks Large dataset of the social structure of Facebook. None. 100 colleges covered Text Network analysis, clustering 2012 [85] [86] A. Traud et al. Dataset for the Machine Comprehension of Text
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]
Cost engineering is "the engineering practice devoted to the management of project cost, involving such activities as estimating, cost control, cost forecasting, investment appraisal and risk analysis". [1] "Cost Engineers budget, plan and monitor investment projects. They seek the optimum balance between cost, quality and time requirements." [2]