Deploy in 115+ regions with the modern database for every enterprise.
MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
Start Free
AI-powered service management for IT and enterprise teams
Enterprise-grade ITSM, for every business
Give your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
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.
...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.
...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 machinelearning. It is not a neural network. And it is still under development.
ApMl provides users with the ability to crawl the web and download pages to their computer in a directory structure suitable for a MachineLearning system to both train itself and classify new documents. Classification Algorithms include Naive Bayes, KNN
Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.
Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
This is my Master Degree project, I am trying to improve the movie prediction by using machinelearning techniques, for the Netflix data set. This project is done under guidance of Dr. Richard Maclin, at University of Minnesota Duluth.