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The datasets are classified, based on the licenses, as Open data and Non-Open data. The datasets from various governmental-bodies are presented in List of open government data sites. The datasets are ported on open data portals. They are made available for searching, depositing and accessing through interfaces like Open API. The datasets are ...
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 ]
A visualization of the email network in the Enron Corpus, with coloring representing eight communities. The corpus is valued as one of the few publicly available mass collections of real emails easily available for study; such collections are typically bound by numerous privacy and legal restrictions which render them prohibitively difficult to access, such as non-disclosure agreements and ...
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.
Fraud detection is a knowledge-intensive activity. The main AI techniques used for fraud detection include: . Data mining to classify, cluster, and segment the data and automatically find associations and rules in the data that may signify interesting patterns, including those related to fraud.
For example, www.paypalsecure.com, includes the name, but is a spoofed URL designed to deceive. Remember to always log into PayPal through a new window browser and never log in through email. In the case that you do receive a suspected spoofed URL, forward the entire email to spoof@PayPal.com to help prevent the URL from tricking other PayPal ...
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
Because side-channel attacks rely on the relationship between information emitted (leaked) through a side channel and the secret data, countermeasures fall into two main categories: (1) eliminate or reduce the release of such information and (2) eliminate the relationship between the leaked information and the secret data, that is, make the leaked information unrelated, or rather uncorrelated ...
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