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Some products in Category:Data analysis software and Category:Statistical software also include data mining and machine learning facilities. Subcategories This category has the following 3 subcategories, out of 3 total.
Software Creator Initial release Software license [a] Open source Platform Written in Interface OpenMP support OpenCL support CUDA support ROCm support [1] Automatic differentiation [2] Has pretrained models Recurrent nets Convolutional nets RBM/DBNs Parallel execution (multi node) Actively developed BigDL: Jason Dai (Intel) 2016 Apache 2.0 ...
Machine learning is a branch of statistics and computer science which studies algorithms and architectures that learn from observed facts. The main article for this category is Machine learning . Wikimedia Commons has media related to Machine learning .
Comet has an approval rating of 44% on review aggregator website Rotten Tomatoes, based on 32 reviews, and an average rating of 5.3/10. [7] Metacritic assigned the film a weighted average score of 52 out of 100, based on 13 critics, indicating "mixed or average reviews". [8] Variety called it a "misfire" but praised the lead performances. [9] /
Direct members of this category should be general-purpose software for training or otherwise interacting with deep learning models. Specific deep learning models, or consumer software applications powered by deep learning, should be placed in Category:Deep learning software applications .
Bayesian methods are introduced for probabilistic inference in machine learning. [1] 1970s 'AI winter' caused by pessimism about machine learning effectiveness. 1980s: Rediscovery of backpropagation causes a resurgence in machine learning research. 1990s: Work on Machine learning shifts from a knowledge-driven approach to a data-driven approach.
Data mining and machine learning software (3 C, 89 P) Pages in category "AI software" The following 37 pages are in this category, out of 37 total.
In early 2000, the software was developed into a client–server model architecture, and shortly afterward, the client front-end interface component was rewritten fully and replaced with a new Java front-end, which allowed deeper integration with the other tools provided by SPSS. SPSS Clementine version 7.0: The client front-end runs under Windows.