Showing 2 open source projects for "machine learning"

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  • Quality and compliance software for growing life science companies Icon
    Quality and compliance software for growing life science companies

    Unite quality management, product lifecycle, and compliance intelligence to stay continuously audit-ready and accelerate market entry

    Automate gap analysis across FDA, ISO 13485, MDR, and 28+ regulatory standards. Cross-map evidence once, reuse across submissions. Get real-time risk alerts and board-ready dashboards, so you can expand into new markets with confidence
    Learn More
  • MaintainX is the world-leading mobile-first workflow management platform for industrial and frontline workers. Icon
    MaintainX is the world-leading mobile-first workflow management platform for industrial and frontline workers.

    Trusted by Operational Leaders Across the Globe

    Your day-to-day maintenance tasks, simplified. MaintainX eliminates the paperwork, so you can spend less time on your clipboard and more time getting things done.
    Learn More
  • 1
    HydraDragonAntivirus

    HydraDragonAntivirus

    Dynamic and static analysis with Sandboxie for Windows, including EDR

    Dynamic and static analysis with Sandboxie for Windows, including EDR, ClamAV, YARA-X, custom machine learning AI, behavioral analysis, NLP-based detection, website signatures, Ghidra, Suricata, Sigma, and much more than you can imagine
    Downloads: 19 This Week
    Last Update:
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  • 2
    Malware Classifier

    Malware Classifier

    Perform quick, easy classification of binaries for malware analysis.

    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. ...
    Downloads: 1 This Week
    Last Update:
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