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New Dell EMC Solutions Bring Machine and Deep Learning to Mainstream Enterprises

Dell EMC announces new machine learning and deep learning solutions, continuing the company’s work to bring high performance computing (HPC) and data analytics capabilities to mainstream enterprises worldwide. This enables organizations to take advantage of the convergence of HPC and data analytics and realize advancements in areas including fraud detection, image processing, financial investment analysis and personalized medicine.

Medial EarlySign Machine Learning Algorithm Predicts Risk for Prediabetics Becoming Diabetic Within 1 year

Medial EarlySign, a developer of machine learning tools for data-driven medicine, announced the results of its clinical data study on identifying and stratifying prediabetic patients at high risk for progressing to diabetes within one year.

Successfully Predict Content Users Will Like Using a Recommendation Engine

Recommendation engines can be used to improve businesses across industries, from media to e-commerce and more. A new report from Dataiku explores the ins and outs of these tools and explores how recommendation engines can be an effective way to drive more eyes to your content.

deepsense.ai Popularizes Machine Learning at European Universities as Part of the Intel Nervana AI Academy

deepsense.ai will train hundreds of European students in the upcoming three months as part of the Intel® Nervana™ AI Academy. Students will get the valuable opportunity to gain practical knowledge in two of the most cutting‑edge and fast developing areas of data science, machine learning and deep learning.

Market to Market: The Return of the CPM

In this contributed article, Yoav Oz, Co-Founder of Spotad, delves into the return of CPM and the events that lead to its crucial comeback. He explains the reasoning for keeping this older, yet necessary, system on the AdTech scene.

Optimizing Machine Learning with Tensorflow, ActivePython and Intel

Through the use of machine learning, unique insights become valuable decision points. As developers consider the varied approaches to leverage machine learning, the role of tools comes to the forefront. Listen to this Gigaom Research webinar that takes a look at the opportunities and challenges that machine learning brings to the development process.

Recommendation Engines: Learn How to Drive More Users to Your Content

A new guide from Dataiku provides a high-level overview of recommendation engines, how they’re built, and how they can be used to improve your business. Download the full report to find out how recommendation engines can be an effective way to drive more eyes to your content.

Python: Unlocking the Power of Data Science & Machine Learning

Python stands out as the language best suited for all areas of the data science and machine learning framework. Designed as a flexible general purpose language, Python is widely used by programmers and easily learnt by statisticians. Download the new guide from ActiveState that provides a summary of Python’s attributes, as well as considerations for implementing the programming language to drive new insights and innovation from big data.

Intel’s New Processors: A Machine-learning Perspective

Machine learning and its younger sibling deep learning are continuing their acceleration in terms of increasing the value of enterprise data assets across a variety of problem domains. A recent talk by Dr. Amitai Armon, Chief Data-Scientist of Intel’s Advanced Analytics department, at the O’reilly Artificial Intelligence conference, New-York, September 27 2016, focused on the usage of Intel’s new server processors for various machine learning tasks as well as considerations in choosing and matching processors for specific machine learning tasks.

MapR Delivers Self-Service Data Science for Leveraging Machine Learning and Artificial Intelligence

MapR Technologies, Inc., a pioneer in delivering one platform for all data, across every cloud, announced the MapR Data Science Refinery, a new solution that provides data scientists an easy way to access and analyze all data in-place, to collaborate, build and deploy machine learning models on the MapR Converged Data Platform.