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PyTorch is a machine learning library based on the Torch library, [4] [5] [6] used for applications such as computer vision and natural language processing, [7] originally developed by Meta AI and now part of the Linux Foundation umbrella.
OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly for real-time computer vision. [2] Originally developed by Intel, it was later supported by Willow Garage, then Itseez (which was later acquired by Intel [3]). The library is cross-platform and licensed as free and open-source software under Apache License ...
The torch package also simplifies object-oriented programming and serialization by providing various convenience functions which are used throughout its packages. The torch.class(classname, parentclass) function can be used to create object factories ().
Major advances in this field can result from advances in learning algorithms (such as deep learning), computer hardware, and, less-intuitively, the availability of high-quality training datasets. [1] High-quality labeled training datasets for supervised and semi-supervised machine learning algorithms are usually difficult and expensive to ...
OpenCV has Python bindings with a rich set of features for computer vision and image processing. [212] Python is commonly used in artificial intelligence projects and machine learning projects with the help of libraries like TensorFlow, Keras, Pytorch, scikit-learn and the Logic language ProbLog.
Apache Lucene, a high-performance, full-featured text search engine library written entirely in Java. [49] Apache OpenNLP, a machine learning based toolkit for the processing of natural language text. It supports the most common NLP tasks, such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking and ...
The adaptive mixtures of local experts [5] [6] uses a gaussian mixture model.Each expert simply predicts a gaussian distribution, and totally ignores the input. Specifically, the -th expert predicts that the output is (,), where is a learnable parameter.
TensorFlow and PyTorch, by far the most popular machine learning libraries, [20] as of 2023 largely only include Adam-derived optimizers, as well as predecessors to Adam such as RMSprop and classic SGD. PyTorch also partially supports Limited-memory BFGS, a line-search method, but only for single-device setups without parameter groups. [19] [21]