Search Results for "machine learning workloads"
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Showing 5 open source projects for "machine learning workloads"
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Veeam Data Platform v13.1Try Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
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Safe Exam Browser is a webbrowser-environment to carry out online-exams safely. The software changes any computer into a secure workstation. It regulates the access to any utilities and prevents students from using unauthorised resources.
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TinyWebServer
Web server framework for Linux
...HTTP request parsing via a state machine capable of processing GET and POST. Tested under high concurrency (Webbench) to support tens of thousands of simultaneous connections. -
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Jarvis Celibi
A smart bot for basic tasks.
...Creating a program to simulate an artificially intelligent computer capable of carrying out simple task. Jarvis Celibi 4.2 is not artificial intelligence. It is not machine learning. It is not a neural network. And it is still under development. -
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ApMl provides users with the ability to crawl the web and download pages to their computer in a directory structure suitable for a Machine Learning system to both train itself and classify new documents. Classification Algorithms include Naive Bayes, KNN
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Paessler: Easy to Use With Enterprise Power. Free TrialYou shouldn't have to choose between a monitoring tool that's easy to use and one that's powerful enough for a complex environment. PRTG's low-code interface lets any admin build dashboards, set alerts and monitor devices without scripting, while custom sensors and full API access are there when your team needs deeper control. One platform, no compromise. Download a free 30-day trial now.
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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.
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