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Parse tree generated with NLTK. The Natural Language Toolkit, or more commonly NLTK, is a suite of libraries and programs for symbolic and statistical natural language processing (NLP) for English written in the Python programming language. It supports classification, tokenization, stemming, tagging, parsing, and semantic reasoning ...
Website with academic papers about security topics. This data is not pre-processed Papers per category, papers archive by date. [379] Trendmicro Website with research, news, and perspectives bout security topics. This data is not pre-processed Reviewed list of Trendmicro research, news, and perspectives. [380] The Hacker News
The library NumPy can be used for manipulating arrays, SciPy for scientific and mathematical analysis, Pandas for analyzing table data, Scikit-learn for various machine learning tasks, NLTK and spaCy for natural language processing, OpenCV for computer vision, and Matplotlib for data visualization. [3]
Download the data dump using a BitTorrent client (torrenting has many benefits and reduces server load, saving bandwidth costs). pages-articles-multistream.xml.bz2 – Current revisions only, no talk or user pages; this is probably what you want, and is over 19 GB compressed (expands to over 86 GB when decompressed).
Provides an RDF data set about scientific publications and related entities, such as authors, institutions, journals, and fields of study. The data set is based on the Microsoft Academic Graph. [105] [106] Free University of Freiburg: MyScienceWork: Science Database includes more than 70 million scientific publications and 12 million patents. Free
Common Crawl is a nonprofit 501(c)(3) organization that crawls the web and freely provides its archives and datasets to the public. [1] [2] Common Crawl's web archive consists of petabytes of data collected since 2008. [3] It completes crawls approximately once a month. [4] Common Crawl was founded by Gil Elbaz. [5]
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
Google announced they had been running TPUs inside their data centers for more than a year, and had found them to deliver an order of magnitude better-optimized performance per watt for machine learning. [24] In May 2017, Google announced the second-generation, as well as the availability of the TPUs in Google Compute Engine. [25]