Splunk ITSI: Adaptive Thresholds and Anomaly Detection

by Jonathan Allen on  Sep 24, 2015

In theory the operations team determines what the thresholds for warnings and alerts should be. But in practice, the operations team often have no idea what these values should be. Using machine learning techniques such as adaptive thresholds, Splunk ITSI solves this problem.

Splunk .conf 2015 Keynote

by Jonathan Allen on  Sep 22, 2015

Splunk opened their big data conference with an emphasis on “making machine data accessible, usable, and valuable to everyone”. This is a shift from their original focus: indexing arbitrary big data sources. Reasonably happy with their ability to process data, they want to ensure that developers, IT staff, and normal people have a way to actually use all of the data their company is collecting.

Microsoft Releases Azure Data Factory

by Richard Seroter on  Aug 25, 2015 1

Any cloud provider that believes in data gravity is trying to make it easier to collect and store data in its facilities. To make data movement between cloud and on-premises endpoints easier, Microsoft recently announced the general availability of Azure Data Factory (ADF).

Deep Convolutional Networks for Super-Resolution Image Reconstruction at Flipboard

by Mikio Braun on  May 26, 2015

Flipboard recently reported on an in-house application of deep learning to scale up low-resolution images that illustrates the power and flexibility of this class of learning algorithms.

Microsoft Project Oxford Aims to Bring Intelligence to Apps

by Sergio De Simone on  May 12, 2015

Under the name of Project Oxford, Microsoft has made available a set of RESTful APIs that aim to make it possible for developers to build apps that feature face recognition, speech processing, and other machine learning algorithms. Part of the Azure portfolio, the new APIs are currently in beta and free to use up to 5,000 call per month.

Facebook Open Sources Modules for Faster Deep Learning on Torch

by Abel Avram on  Jan 20, 2015

Facebook has open sourced a number of modules for faster training of neural networks on Torch.

Google on the Technical Debt of Machine Learning

by Mikio Braun on  Jan 15, 2015

A number of Google researchers and engineers presented their view on the technical debt of using machine learning at a NIPS workshop. They identified different aspects of technical debt and came to the conclusion that without proper care, using machine learning or complex data analysis in your company can induce new kinds of technical debt different from classical software engineering.

Google Uses Machine Learning to Simplify CAPTCHA

by Abel Avram on  Dec 03, 2014

Google has announced a new CAPTCHA API which provides a No CAPTHA experience for most users.

Web Summit 2014 Day One Review

by Alex Giamas on  Nov 04, 2014

Web Summit, one of the largest technology conferences in Europe opened up today. Famous people from the technology and business world are expected to talk, like Peter Thiel, Drew Houston and Anna Patterson.

Microsoft Expands Azure Machine Learning and Real Time Analytics Offering

by Alex Giamas on  Oct 31, 2014

Microsoft recently announced new machine learning capabilities for Microsoft Azure platform. Developers can also create their own web services and publish them to Azure Marketplace. Microsoft also announced availability of Apache Storm for Azure. Azure Stream Analytics, Data Factory and Event Hubs for Azure were all announced in the past few weeks by Microsoft. In this article we explore moreabout

LinkedIn and Twitter Contribute Machine Learning Libraries to Open Source

by Alex Giamas on  Oct 24, 2014

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.

Nvidia Introduces cuDNN, a CUDA-based library for Deep Neural Networks

by Jérôme Serrano on  Sep 29, 2014

Nvidia earlier this month released cuDNN, a set of optimized low-level primitives to boost the processing speed of deep neural networks (DNN) on CUDA compatible GPUs. The company intends to help developers harness the power of graphics processing units for deep learning applications.

Microsoft Launching Azure Machine Learning as a Service

by Alex Giamas on  Sep 16, 2014

Microsoft recently announced Azure ML, a machine learning cloud based platform that helps predict future events based on past performance. Microsoft has been using machine learning for years for Bing, Xbox and other products but this is the first time that internal technologies are consumerized and deployed as cloud services. Ersatz Labs is also trying to build a PaaS for Machine Learning.

Domino: Datascience-as-a-Service

by Michael Hausenblas on  Mar 11, 2014

Domino, a Platform-as-a-Service for data science, enables people to do analytical work using languages such as Python or R in the cloud (EC2).

Spark Officially Graduates From Apache Incubator

by Alex Giamas on  Feb 28, 2014

Recently, Spark graduated from the Apache incubator. Spark claims up to 100x speed improvements over Apache Hadoop over in-memory datasets and gracefully falling back to 10x speed improvement for on-disk performance. Based on Scala, it can run SQL queries and be used directly in R. It provides Machine Learning, Graph database capabilities and other further discussed in the article.

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