798 search results for "register"

Making an R Package to use the HERE geocode API

October 23, 2014
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HERE is a product by Nokia, formerly called Nokia maps and before that, Ovi maps. It's the result of the acquisition of NAVTEQ in 2007 combined with Plazes and Metacarta, among others. It has a geocoding API, mapping tiles, routing services, and other things. I'm focused on the geocoding service. Under the “Base” license,...

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Analyze Instagram with R

October 13, 2014
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Analyze Instagram with R

This tutorial will show you how you create an Instagram app, create an authentication process with R and get data via the Instagram API. There is no R package for this yet so we... The post Analyze Instagram with R appeared first on ThinkToStart.

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Deploying Shiny apps with shinyapps.io

October 10, 2014
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So I’ve been messing around with Shiny for a year or so now. It’s great tool and getting greater. the good: capability to rapidly build an interactive visualization with the full universe of R packages to choose from for the computation engine and visualization options. ability to code and house the visualization/app in the same language/place as the code...

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Building a DGA Classifier: Part 3, Model Selection

October 6, 2014
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Building a DGA Classifier: Part 3, Model Selection

This is part two of a three-part blog series on building a DGA classifier and it is split into the three phases of building a classifier: 1) Data preparation 2) Feature engineering and 3) Model selection (this post) Back in part 1, we prepared the data and we are starting with a nice clean list of domains labeled as either legitimate (“legit”) or generated by an algorithm (“dga”)....

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By-Group Aggregation in Parallel

October 4, 2014
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By-Group Aggregation in Parallel

Similar to the row search, by-group aggregation is another perfect use case to demonstrate the power of split-and-conquer with parallelism. In the example below, it is shown that the homebrew by-group aggregation with foreach pakage, albeit inefficiently coded, is still a lot faster than the summarize() function in Hmisc package.

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Building a DGA Classifier: Part 1, Data Preparation

September 30, 2014
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This will be a three-part blog series on building a DGA classifier and will be split into three logical phases of building a classifier: 1) Data preparation (this) 2) Feature engineering and 3) Model selection. And before I get too far into this, I want to give a huge thank you to Click Security for releasing a DGA classifier in python as part of...

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Registration now open for Master R Developer workshop in San Francisco

September 29, 2014
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Registration now open for Master R Developer workshop in San Francisco

Registration is now open for the next Master R Development workshop led by Hadley Wickham, author of over 30 R packages and the Advanced R book. The workshop will be held on January 19 and 20th in the San Francisco bay area. The workshop is a two day course on advanced R practices and package

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Row Search in Parallel

September 28, 2014
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Row Search in Parallel

I’ve been always wondering whether the efficiency of row search can be improved if the whole data.frame is splitted into chunks and then the row search is conducted within each chunk in parallel. In the R code below, a comparison is done between the standard row search and the parallel row search with the FOREACH

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Webinar September 25: Data Science with R

September 19, 2014
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A quick heads up that if you'd like to get a great introduction to doing data science with the R language, Joe Rickert will be giving a free webinar next Thursday, September 25: Data Science with R. Regular readers of the blog will be familiar with Joe's posts on this topic. A few recent examples include posts on comparing...

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Comparing machine learning models in R

September 18, 2014
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Comparing machine learning models in R

by Joseph Rickert While preparing for the DataWeek R Bootcamp that I conducted this week I came across the following gem. This code, based directly on a Max Kuhn presentation of a couple years back, compares the efficacy of two machine learning models on a training data set. #----------------------------------------- # SET UP THE PARAMETER SPACE SEARCH GRID ctrl <-...

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