A fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning
H2O makes Hadoop do Math! H2O scales statistics, machine learning and math over Big Data. H2O keeps familiar interfaces like R, Excel & JSON so that big data enthusiasts and experts can explore, munge, model and score data sets using a range of simple to advanced algorithms.
Fast and optimized pages lead to higher visitor engagement, retention, and conversions. The PageSpeed family of tools is designed to help you optimize the performance of your website. PageSpeed Insights products will help you identify performance best practices that can be applied to your site, and PageSpeed optimization tools can help you automate the process.
Apache Storm is a distributed, fault tolerant, and scalable platform for processing streaming data, supporting real-time analytics and machine learning.
On September 17, the Apache Software Foundation (ASF) voted to graduate Apache Storm to a top-level project (TLP). This represents a major step forward for the project and represents the momentum built by a broad community of developers from not only Hortonworks, but also Yahoo!, Alibaba, Twitter, Microsoft and many other companies.
In-memory big data has come of age. Spark platform with it’s elegant API and architecture has captured developer’s hearts. Machine learning as an API for big data is just as real. R and predictive analytics on Big Data has become the center of the space. H2O has established a leadership in scalable ML having focused over the past two years. Spark captured developer’s hearts and minds of developers at the same time.
Sparkling Water brings together best of the both worlds!
Dedicated Team Blog for the Windows Server and Cloud Division to discuss Windows Server and the underlying technologies and workloads like Hyper-V - Virtualization, Private Cloud, Remote Desktop Services - RDS - Terminal Server, Virtual Desktop Infrastructure - VDI, Active Directory - AD, Group Policy, Windows Storage Server, Small Business Server - SBS, Windows HPC Server, Powershell, Management Infrastructure
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Twitter’s engineering group, known for various contributions to open source from streaming MapReduce to front-end framework Bootstrap recently announced open sourcing an algorithm that can efficiently recommend content. LinkedIn also open sourced a Machine Learning library of its own, ml-ease. In this article we present the algorithms and what they mean for the open source community.
Today, we announced an exciting set of joint initiatives with Microsoft, including:
Extending Docker to Windows with Docker Engine for Windows ServerMicrosoft’s support of Docker’s open orchestration APIsIntegration of Docker Hub with Microsoft Azure, andCollaboration on the multi-Docker container model, including support for applications consisting of both Linux and Windows Docker containers
I’d like to provide some context for this announcement, and why we are so excited.
During photosynthesis, plants only convert about 10% of the light they receive from the sun into usable hydrogen to fuel the reaction. Last summer, a group of researchers were able to break the world record for laboratory efficiency by reaching 44.7% with a new cell, with 50% as the ultimate goal.
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