333 search results for "hadoop"

Product revenue prediction with R – part 1

October 8, 2012
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Product revenue prediction with R – part 1

In my upcoming three blogs, I am going to discuss about how Product managers, Data analyst and Data scientists can develop model for the prediction of the transactional product revenue on the basis of user actions like total numbers of time product added to the cart, total numbers of time product added to the cart,

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Tips on accessing data from various sources with R

October 3, 2012
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Jeffrey Breen (the man behind the Twitter airline sentiment analysis example) recently posted a collection of slides with some great tips for accessing data from R. "Tapping the Data Deluge" includes information on: Using the XLConnect package to read data from Excel spreadsheets Using the foreign package to read SPSS, SAS, Stata and dBase data files Using SQL queries...

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Oracle R Enterprise Tutorial Series on Oracle Learning Library

October 2, 2012
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Oracle Server Technologies Curriculum has just released the Oracle R Enterprise Tutorial Series, which is publicly available on Oracle Learning Library (OLL). This 8 part interactive lecture series with review sessions covers Oracle R Enterprise ...

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Predict Bounce Rate based on Page Load Time in Google Analytics

September 26, 2012
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Predict Bounce Rate based on Page Load Time in Google Analytics

Welcome to the second part. In the last blog post on Linear Regression with R, we have discussed about what is regression? and how it is used ? Now we will apply that learning on a specific problem of prediction. In this post, I will create a basic model to predict bounce rate as function

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Linear Regression using R

September 26, 2012
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Linear Regression using R

Regression Through this post I am going to explain How Linear Regression works? Let us start with what is regression and how it works? Regression is widely used for prediction and forecasting in field of machine learning. Focus of regression is on the relationship between dependent and one or more independent variables. The “dependent variable”

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The PMML Revolution: Predictive analytics at the speed of business

September 19, 2012
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The PMML Revolution: Predictive analytics at the speed of business

This guest post is by Alex Guazzelli, VP of Analytics at Zementis Inc. -- ed. PMML, the Predictive Model Markup Language, is the de facto standard to represent predictive analytics and data mining models. With PMML, it is extremely easy to move a predictive solution from one system to another, since it avoids proprietary issues and incompatibilities. Companies around...

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Tips for Making R User Group Videos

September 17, 2012
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Tips for Making R User Group Videos

Today's guest post is from Ron Fredericks, videographer and co-founder of LectureMaker, LLC — ed. I was initially surprised to find R user groups (RUGs) so popular. I filmed my first R session during the 2009 Predictive Analytics World in San Francisco. I filmed several more R user sessions over the past three years along with business/science clients and...

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In case you missed it: August 2012 Roundup

September 6, 2012
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In case you missed them, here are some articles from June of particular interest to R users. RStan is a new package for Bayesian modeling with R. It's faster and can fit more highly-correlated models than the MCMC sampler of BUGS and JAGS. Biostatistician Corey Chivers used R to animate the epidemic-like growth of retailer Walmart in the US....

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Thalesians, and other events

September 5, 2012
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Thalesians, and other events

Featured Thalesians, London 2012 September 12. Chia Tan on “Practical Financial Modeling”. Abstract: Financial modelling is not a competition in the mastery of complexity. Rather, the aim is to come up with the simplest models adequate to capture salient market features of traded products. There exists a wide gulf between material covered by traditional books … Continue reading...

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Can Anyone Become a Data Scientist? Oxdata Believes So

August 21, 2012
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Can Anyone Become a Data Scientist? Oxdata Believes So

Data science is a sophisticated and complex discipline, but since it's still an emerging field, its practitioners come from a wide variety of backgrounds. Typically, though, a background in working with large data sets in a research setting is advantageous. This is why you may be mingling with a former physicist or immunologist at the next data hackathon...

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