Compliant and Reliable File Transfers Backed by Top Security Certifications
Cerberus FTP Server delivers SOC 2 Type II certified security and FIPS 140-2 validated encryption.
Stop relying on non-certified, legacy file transfer tools that creak under the weight of modern security demands. Get full audit trails, advanced access controls and more supported by an award-winning team of experts. Start your free 25-day trial today.
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Enterprise-grade ITSM, for every business
Give your IT, operations, and business teams the ability to deliver exceptional services—without the complexity.
Freshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
Strong Email & Apache Log Analysis with Active Security Features
...Module renamed "X-Itools ELSE", for "X-Itools E-mail Log Search Engine". Some features: Log analysis and correlation of Postfix and Exchange servers, statistics, policy manager, in-deep analysis, automated network graphs for e-mail tracing, CSV export... The Swiss knife of Messaging Admins.
In 2015, X-Itools ELSE is no more limited to E-mail logs: Apache logs are also processed and related stats and dashboards will be there!
Free Syslog Server for Windows with a graphical user interface
Visual Syslog Server for Windows is a free open source program to receive and view syslog messages.
Useful when setting up routers and systems based on Unix/Linux.
Visual Syslog Server for Windows has a live messages view: switches to a new received message. Helpful color highlighting.
Useful message filtering. Customizable notification and actions.
Sources hosted on the GitHub:
https://github.com/MaxBelkov/visualsyslog
This is my Master Degree project, I am trying to improve the movie prediction by using machine learning techniques, for the Netflix data set. This project is done under guidance of Dr. Richard Maclin, at University of Minnesota Duluth.