Tag: News

Feed: R-bloggers. Author: Thinking inside the box. A new maintenance release of the nanotime package for working with nanosecond timestamps just arrived on CRAN. nanotime uses the RcppCCTZ package for (efficient) high(er) resolution time parsing and formatting up to nanosecond resolution, and the bit64 package for the actual integer64 arithmetic. Initially implemented using the S3 system, it now uses a more rigorous S4-based approach thanks to a rewrite by Leonardo Silvestri. This release re-disables tests for xts use. At some point we had hoped a new xts version would know what nanotime is. That xts version is out now, and ... Read More

Feed: AWS Partner Network (APN) Blog. Author: Renata Melnyk. The AWS Competency Program welcomed 22 new AWS Partner Network (APN) Partners in June—spanning workload, solution, and industry designations. Please join us in welcoming our newest AWS Competency Partners!The AWS Competency Program helps customers identify and choose the world’s top APN Partners that have demonstrated technical proficiency and proven customer success in specialized solution areas. To receive the AWS Competency designation, APN Partners must undergo rigorous technical validation related to industry-specific technology, as well as an assessment of the security, performance, and reliability of their AWS solutions. This validation gives customers complete confidence in choosing APN Partner ... Read More

Feed: R-bloggers. Author: xi'an. A griddy Le Monde mathematical puzzle: On a 4×5 regular grid, find how many nodes need to be turned on to see all 3×4 squares to have at least one active corner in case of one arbitrary node failing.  Repeat for a 7×9 grid. The question is open to simulated annealing, as in the following R code: n=3;m=4;np=n+1;mp=m+1 cvr=function(grue){ grud=grue obj=(max(grue)==0) for (i in (1:length(grue))[grue==1]){ grud[i]=0 obj=max(obj,max((1-grud[-1,-1])*(1-grud[-np,-mp])* (1-grud[-np,-1])*(1-grud[-1,-mp]))) grud[i]=1} obj=99*obj+sum(grue) return(obj)} dumban=function(grid,T=1e3,temp=1,beta=.99){ obj=bez=cvr(grid) sprk=grid for (t in 1:T){ grue=grid if (max(grue)==1){ grue[sample(rep((1:length(grid))[grid==1],2),1)]=0 }else{ grue[sample(1:(np*mp),np+mp)]=1} jbo=cvr(grue) if (bez>jbo){ bez=jbo;sprk=grue} if (log(runif(1)) leading to > dumban(grid,T=1e6,temp=100,beta=.9999) $top [1] ... Read More

Feed: News & Blog – Logicworks. Author: Logicworks; It seems that every month, another healthcare company is hacked. In fact, 1.13M records were exposed by 110 healthcare data breaches in Q1 2018 alone.Why the constant parade of security flaws? Why is the theft of millions of health records so commonplace?At Logicworks, we’ve spent the last 25 years helping companies prepare for – and defend against – potential attacks. Here are five reasons why this problem won’t just go away.1. Systems are old and complexThe biggest reason healthcare companies are not paying more attention to cybersecurity is exactly what you’d expect: ... Read More

Feed: R-bloggers. Author: Carmen Chan. Installing R package Because flipAPI does not require external libraries that use Java or Perl, installation is very straightforward. Simply open R and type the following into the console: install.package(devtools) devtools::install_github("Displayr/flipAPI") Once the flipAPI package is installed, a file can be read in by using the command library(flipAPI) DownloadXLSX(filename) Data output format In many cases, the Excel format contains multiple tables with comments and other text. It is not necessary to reformat the file before importing. We can specify particular sheets or ranges to import. cola1 = DownloadXLSX("https://wiki.q-researchsoftware.com/images/b/b9/Cola_Discriminant_Functions.xlsx", want.col.names = TRUE, range = "A2:G9") cola2 ... Read More

Feed: Google Cloud Big Data and Machine Learning Blog. Author: Google Cloud Big Data and Machine Learning Blog Team. Innovation in data processing and machine learning technology Developing a JanusGraph-backed Service on Google Cloud Platform Thursday, July 19, 2018 By Ted Wilmes, Data Architect at Expero, JanusGraph Technical Steering Committee, Apache TinkerPop Project Management Committee The graph database space is rapidly expanding as more and more companies identify potential use cases that require the traversal of highly connected network and hierarchical data sets in ways that are cumbersome with RDBMSs and NoSQL solutions. Today we’ll explore this graph database landscape ... Read More

Feed: News & Blog – Logicworks. Author: Logicworks; AWS Summit NY 2018. Photo Credit: LogicworksAWS has launched over a thousand major service updates in 2018 and launched nearly a dozen new services. (And it’s only July.)As services are announced, the team at Logicworks immediately starts trying out new features and discussing them with clients. Here are the services that our AWS Certified Engineers are talking about from the last quarter: AWS Landing ZoneAWS Landing Zone is a service that automates the set-up of a multi-account AWS environment, by helping you implement an initial security baseline across AWS IAM, data security, ... Read More

Feed: R-bloggers. Author: R Views. In previous posts, we covered how to run a Monte Carlo simulation and how to visualize the results. Today, we will wrap that work into a Shiny app wherein a user can build a custom portfolio, and then choose a number of simulations to run and a number of months to simulate into the future. A link to that final Shiny app is here and here is a snapshot: We will use RMarkdown to build our Shiny application by inserting runtime: shiny into the yaml header. This will alert the server (or our laptop) that ... Read More

Feed: R-bloggers. Author: Abdul Majed Raja. It could be the era of Deep Learning where it really doesn’t matter how big is your dataset or how many columns you’ve got. Still, a lot of Kaggle Competition Winners and Data Scientists emphasis on one thing that could put you on the top of the leaderboard in a Competition is “Feature Engineering”. Irrespective of how sophisticated your model is, good features will always help your Machine Learning Model building process better than others. What is Feature engineering? Features are nothing but columns/dimensions and Feature Engineering is the process of creating new Features ... Read More

Feed: R-bloggers. Author: Laura Swales. We are delighted to announce that the full EARL US Roadshow agendas are now available! Each city has a different line-up of world-class speakers and R experts for you to explore. EARL focuses on the business application of R and will showcase many fascinating and inspiring use cases from a range of industry sectors. We wanted to share with you just some of the talks we are looking forward to in each city: Seattle – 7 November See the full agenda. R use cases: Examining influence of roadway design features on drivers’ speed choice in ... Read More