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Machine Learning: Why it Matters?

In this contributed article, Smita Adhikary, Managing Consultant at Big Data Analytics Hires, provides a whirlwind overview of machine learning technology and why it’s important to increasing the value of enterprise data assets.

IBM Brings Machine Learning to the Private Cloud

IBM announced IBM Machine Learning, the first cognitive platform for continuously creating, training and deploying a high volume of analytic models in the private cloud at the source of vast corporate data stores. Even using the most advanced techniques, data scientists – in shortest supply among today’s IT skills* – might spend days or weeks […]

Dr. Eng Lim Goh on New Trends in Big Data and Deep Learning for Artificial Intelligence

In this video from SC16, Dr. Eng Lim Goh from HPE/SGI discusses new trends in HPC Energy Efficiency and Deep Learning for Artificial Intelligence. “Recently acquired by Hewlett Packard Enterprise, SGI is a trusted leader in technical computing with a focus on helping customers solve their most demanding business and technology challenges.”

ExtraHop Introduces Addy: Cloud-Based Machine Learning for Data-Driven IT

ExtraHop, the leader in real-time IT analytics, today announced ExtraHop Addy, the industry’s first cloud service that applies machine learning to the richest source of IT data—wire data—to provide real-time situational insight for IT teams. ExtraHop Addy is always-on, serving as the eyes and ears for IT and helping them take a proactive, data-driven approach to supporting and securing the digital experience.

The Difference between AI, Machine Learning and Deep Learning

The insideBIGDATA Guide to Deep Learning & Artificial Intelligence is a useful new resource directed toward enterprise thought leaders who wish to gain strategic insights into this exciting area of technology. This is the second in a series of articles providing content extracted from the guide. The topic for this segment is the difference between AI, machine learning and deep learning.

Skytree Patented Automation Gets Smarter and Enables Us to Deliver Machine Learning as a Service with the Release of Skytree 16.0

Skytree, a leader in enterprise machine learning on big data, announces the release of Skytree 16.0 and Skytree’s Machine Learning as a Service offering. We continue our trend of increasing ease of use via unprecedented automation, further enabling non-data scientist users to access the power of enterprise grade machine learning, gain insights, and to add value to their business.

Nimbix Unveils Expanded Cloud Product Strategy for Enterprises and Developers

Nimbix, a leading provider of high performance and cloud supercomputing services, announced its new combined product strategy for enterprise computing, end users and developers. This new strategy will focus on three key capabilities – JARVICE™ Compute for high performance processing, including Machine Learning, AI and HPC workloads; PushToCompute™ for application developers creating and monetizing high performance workflows; and MaterialCompute™, a brand new intuitive user interface, featuring the industry’s largest high performance application marketplace available from a cloud provider.

Booz Allen & Kaggle Convene Data Scientists, Medical Community to Improve Cancer Screening using Artificial Intelligence through $1 Million Competition

Two out of every five people in the U.S. will be diagnosed with cancer during their lifetimes, according to the National Cancer Institute (NCI). The same technology behind improved voice assistants and credit card fraud detection—artificial intelligence—can help improve cancer screening and save lives. Booz Allen Hamilton (NYSE: BAH) and Kaggle announced that the third annual Data Science Bowl will inspire data scientists and medical communities around the world to use artificial intelligence to improve lung cancer screening technology.

Cross-Channel Advertising with Large-Scale Consumer Graphs

In this contributed article, Deb Ray, Chief Data Officer at VideoAmp discusses an important technique where the complexity of cross-channel targeting and measurement is solved by building a large-scale graph of consumers and their connected devices.

Survey of Available Machine Learning Frameworks

The presentation below, “Survey of Available Machine Learning Frameworks,” is provided by Brendan Herger of CapitalOne as part of the H2O World 2015 conference. Learning a new modeling framework is time consuming, and doesn’t always pay off. However, as more feature engineering and modeling frameworks become available, its difficult not to leverage their abilities.