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This project implements in C++ a bunch of known Neural Networks. So far the project implements: LVQ in several variants, SOM in several variants, Hopfield network and Perceptron. Other neural network types are planned, but not implemented yet. The project can run in two modes: command line tool and Python 7.2 extension. Currently, Python version appears more functional, as it allows easy interaction with algorithms developed by other people.

Adobe Malware Classifier is a command-line tool that lets antivirus analysts, IT administrators, and security researchers quickly and easily determine if a binary file contains malware, so they can develop malware detection signatures faster, reducing the time in which users' systems are vulnerable. Malware Classifier uses machine learning algorithms to classify Win32 binaries – EXEs and DLLs – into three classes: 0 for “clean,” 1 for “malicious,” or “UNKNOWN.” The tool was developed using models resultant from running the J48, J48 Graft, PART, and Ridor machine-learning algorithms on a dataset of approximately 100,000 malicious programs and 16,000 clean programs. ...