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Data Science 101: Deep Learning Methods and Applications

Microsoft_machine_learning

Microsoft Research, the research arm of the software giant, is a hotbed of data science and machine learning research. Microsoft has the resources to hire the best and brightest researchers from around the globe. A recent publication is available for download (PDF): “Deep Learning: Methods and Applications” by Li Deng and Dong Yu, two prominent researchers in the field.

Revolution Analytics and AWS Join Forces

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Amazon Web Services (AWS) now offers a hosted version copy of Revolution R Enterprise 7, providing an easy way for individuals and organizations to start and test their big-data-styled analysis projects.

Data Science 101: Building Your Data Science Toolbox

Jeremy Howard made a presentation to the Melbourne R meetup group, where he gave a brief overview of his “data scientist’s toolbox” (using a few Kaggle competitions as practical examples), and also provided an introduction to ensembles of decision trees (including the well-known Random Forest™ algorithm).

Data Science 101: 250 Years of Bayes Theory

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It’s been more than 250 years since the appearance of Bayes theorem (named after English statistician, philosopher and Presbyterian minister Thomas Bayes: 1701-1761), one of the two fundamental inferential principles of mathematical statistics.

Learning Data Science in Total Immersion

Zipfian

San Francisco based Zipfian Academy approaches data science education the way some approach learning a new language – total immersion. The company offers a 12-week intensive advanced data science training program in a modern lab environment.

Doing Data Science in the Cloud with Domino

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As a practicing data scientist and big data journalist, I often find myself down in the trenches on pursuit of new trends, products, and services. Earlier this week I attended a local machine learning meetup group event and I came away with a real gem. The presenter mentioned in passing a new cloud service called “Domino” and I rushed back to my office to learn more. I wasn’t disappointed.

Becoming a Data Scientist – What Does it Take?

I’ve been monitoring a curious and lively discussion over on LinkedIn – “Is it necessary to have a Masters Degree to become a data scientist?” The comments I’ve seen have exhibited a number of points of view on the matter that I think are reflective of the questions on many people’s minds – both those wanting to become a data scientist and those wanting to hire a data scientist.

How Companies are Using Spark

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The video below comes to us from the Strata Conference 2014: How Companies are Using Spark, and Where the Edge in Big Data Will Be. While the first big data systems made a new class of applications possible, organizations must now compete on the speed and sophistication with which they can draw value from data. […]

The New York Times Hires a Chief Data Scientist

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Demonstrating a new sense of relevancy if not urgency for applying data science to a wide cross section of industries, The New York Times has hired Columbia University applied mathematician Chris Wiggins as its first “chief data scientist.”

H2O and Cloudera Team Up to Deliver In-Memory Predictive Analytics

H2O, the open source in-memory machine learning and predictive analytics company for big data, announced a partnership with Cloudera, a leader in enterprise data management powered by Apache™ Hadoop.