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Ask a Data Scientist: Unsupervised Learning

Dr. Andrew W. Wicker, Data Scientist,  Intel Corporation

Welcome back to the “Ask a Data Scientist” article series. This week’s question is from a reader who asks for an overview of unsupervised machine learning.

How to Become a Data Scientist in 8 Easy Steps

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Our friends over at DataCamp just came out with a cool new infographic entitled “Become a Data Scientist in 8 easy steps.” This hits home to a lot of people who are trying to enter this new industry hoping to satisfy a lot of unfilled job openings. The question is how best to make this transition. The useful infographic below will help answer this question by outlining the process of becoming a data scientist.

Interview: Spencer Greenberg, Chairman, Rebellion Research

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In the interview below, Rebellion Research’s Chairman Spencer Greenberg discusses how he feels his company is well-positioned for bringing machine learning and AI based asset management to investors.

Ask a Data Scientist: The Data Science Process

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Welcome back to our series of articles sponsored by Intel – “Ask a Data Scientist.” This week’s question is from a reader who wonders if there is a general process for conducting data science projects.

Deep Learning, Self-Taught Learning and Unsupervised Feature Learning

The video presentation below is a highly compelling talk by Stanford University professor and Coursera co-founder, Dr. Andrew Ng. Andrew addresses a graduate summer school audience at UCLA’s IPAM (Institute for Pure & Applied Mathematics) on the topic – Deep Learning, Feature Learning.

Data Science 101: Data Agnosticism – Feature Engineering Without Domain Expertise

From the SciPy2013 conference, here is a compelling talk “Data Agnosticism: Feature Engineering Without Domain Expertise” by Nicholas Kridler of Accretive Health in Chicago.

Ask a Data Scientist: The Bias vs. Variance Tradeoff

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Welcome back to our series of articles sponsored by Intel – “Ask a Data Scientist.” This week’s question is from a reader who wants an explanation of the “bias vs. variance tradeoff in statistical learning.”

Revolution Analytics Introduces Revolution R Open and Revolution R Plus

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Revolution Analytics, the only commercial provider of open source R software, today announced two new offerings that support the open source R community and elevate R’s capabilities to enterprise-level performance. Revolution R Open is a free, open source R distribution that enhances R performance, makes it easier to share R scripts and improves collaboration on R-based advanced analytics applications.

Ask a Data Scientist: Curse of Dimensionality

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Welcome back to our series of articles sponsored by Intel – “Ask a Data Scientist.” Once a week you’ll see reader submitted questions of varying levels of technical detail answered by a practicing data scientist – sometimes by me and other times by an Intel data scientist. This week’s question is from a reader who wants to know more about the “curse of dimensionality.”

RapidMiner Moves Predictive Analytics, Data Mining and Machine Learning into the Cloud

Pioneering predictive analytics leader RapidMiner has announced the general availability of RapidMiner Cloud.