General-purpose, compute-optimized, or GPU/TPU-accelerated. Built to your exact specs.
Live migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Build Securely on Azure with Proven Frameworks
Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.
Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
ConDEnSE (Confidential Data Enabled Statistical Exploration) will be a web-based environment for statistical analysis of confidential data from various database sources, based on Plone and R, and using the Jackknife method of confidentiality protection.
PMML-compliant scoring engine and analytic toolkit
Augustus development has moved to google code. The new project page is augustus.googlecode.com. New releases of the project are not currently being released to sourceforge.
Augustus is designed for statistical and data mining models and produces and consumes models with 10,000s of segments.
Versions of Augustus support PMML 3, 4.0.1, and 4.1.
Helps compatibility with Vernier's Graphical Analysis and Logger Pro software. Includes a converter to extract important data out of Vernier .ga3 and .cmbl data files, and spreadsheet to analyze the data with tables, graphs, and curve fitting.
The Simple Versatile Plotting (SVP) tools create camera-ready plots of performance analysis data gathered from high performance computing (HPC) applications.
A lightweight, browsing-based, 100% Python, federated data integration framework. Users may create custom schemas for disparate sources, query and expand results across sources to find related data; for use in fields such as bioinformatics and datamining
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.
StrATo (Strain Analysis Tool) loads GE Vingmed heart strain value reports file and performs a statistical peak analysis and curve uniformity evaluation, cutting off sampled noise, plotting results and offering a printout to attach in medical reports.
A windrose, also know as polar rose plot, is a special diagram for representing the distribution of meteorological datas, typically wind speeds by class and direction.
The Model Interaction Environment for Neuroscience provides tools for development, searching, editing, execution, and visualization of biophysical models, abstract mathematical models, and experimental protocols used in neuroscience research.
This is a Python package designed to process Penn Treebank Release II-style combined trees (.mrg files) into useful objects for tree traversal, feature extraction, and statistical analysis. For more information, go to http://mrgutils.sourceforge.net
The Serial Data Acquisition is a lightweight data acquisition system able to parse a vast majority of mostly unidirectional streams. Results are saved in a SQLite DB and accessible over XML-RPC or plain HTTP. Its design is modular and easily extendable.
Using this plugin-based framework, you can instantly start working on the *brain* of your bot (irc bot, chatterbot, robot, ...). With support for db, irc, logging and programming-language independent plugins, users can easily enhance the functionality.
Poor Man's HPC is a framework that allows distributing and running code on a server farm. pmHPC is a scaled down and simplified version of distributed computing projects such as SETI, so is a perfect fit for enthusiasts and universities.
Design and develop Recommendation and Adaptive Prediction Engines to address eCommerce opportunities. Build a portfolio of engines by creating and porting algorithms from multiple disciplines to a usable form. Try to solve NetFlix and other challenges.