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Data Science 101: Support Vector Machines

Support Vector Machines (SVM) is an important and widely used machine learning algorithm. In order to fully understand SVMs, you need to have a fundamental understanding of how the statistical learning method functions. Here is a useful lecture on SVM coming from MIT OpenCourseware.

Ask a Data Scientist: Unsupervised Learning

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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 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.”