Yesterday in Data Science – March 28th 2017

My family and I love boardgames.  We are also on the lookout for new ones that would fit with the ones we already like to play.  So I decided to create a boardgame recommendation websitehttps://larrydag.shinyapps.io/boardgame_reco/I built it using R.  The recommendation engine uses a very simple collaborative filtering algortihm based on correlation scores from other boardgame players collection lists.  The collections are gathered using the API from BoardgameGeek.com.  It is very much in a beta project phase as I just wanted to get something built to get working. I also wanted another project to build in Shiny.  I really like how easy it is to publish R projects with Shiny. Some of the features include:Ability to enter your own collectionGet recommendation on your collectionAmazon link to buy boardgame that is recommendedIts a work in progress.  There is much to clean up and to make more presentable.  Please take a look and offer comments to help improve the website.
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Le Monde mathematical puzzle launched a competition to celebrate its 1000th puzzle! A fairly long-term competition as it runs over the 25 coming puzzles (and hence weeks). Starting with puzzle #1001. Here is the 1000th puzzle, not part of the competition: Alice & Bob spend five (identical) vouchers in five different shops, each time buying […]
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Redmonk have once again updated (a little later than usual) their bi-annual programming language report with their January 2017 rankings. If you haven’t come across these rankings before, they are based on GitHub contributions and StackOverflow questions related to around 40 commonly-used programming languages. The raw data (as of January 2017) is shown below — as you might guess from the appearance of the chart, the analysis for the rankings is done in R. Languages used by data scientists rank highly in this metric. Python is ranked #3 (up from #4 in the June 2016 rankings). R is ranked #14,…
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@eddelbuettel’s idea is a good one. (it’s a quick read…jump there and come back). I often wait for a complete example or new package announcement to blog something when a briefly explained snippet might have sufficient utility for many R users. Also, tweets are fleeting and twitter could end up on the island of misfit… Continue reading →
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In order to get the discount, simply click choose a link below and when paying use the promo code: ENDMARCH10 Udemy is offering readers of R-bloggers access to its global online learning marketplace for only $10 per course! This deal (offering over 50%-90% discount) is for hundreds of their courses – including many R-Programming, data science, machine learning etc. Click here to browse ALL (R and non-R) courses Advanced R courses:  The Comprehensive Programming in R Course (25 Hours of video) Bayesian Computational Analyses with R (12 Hours of video) R Programming for Simulation and Monte Carlo Methods (12 Hours of video) Applied Multivariate Analysis with R (13 Hours of video) Linear Mixed-Effects Models with R (11 Hours of video) Graphs in R (ggplot2, plotrix, base R) – Data Visualization with R Programming Language (5 Hours of video) Multivariate Data Visualization with R (7 Hours of video) More Data Mining with R (11 Hours of video) Text Mining, Scraping and Sentiment Analysis with R (4 Hours of video) Programming Statistical Applications in R (12 Hours of video) Comprehensive Linear Modeling with R (15 Hours of video) Time Series Analysis and Forecasting in R (3 Hours of video) Introductory R courses:  Introduction to R (15 Hours of video) Applied Data Science with R (11 Hours of video) R Level 1 – […]
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Speaking publicly about your data science projects is one of the best things you can do for your portfolio. Writing your presentation will help you refine…
The post How to Reach More People with your Next Data Science Talk appeared first on AriLamstein.com.
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Data science enhances people’s decision making. Doctors and researchers are making critical decisions every day. Therefore, it is absolutely necessary for those people to have some basic knowledge of data science. This series aims to help people that are around medical field to enhance their data science skills. We will work with a health related […]
Related exercise sets:Data science for Doctors: Inferential Statistics Exercises (part-2)
Data Science for Doctors – Part 4 : Inferential Statistics (1/5)
Data Science for Doctors – Part 2 : Descriptive Statistics
Explore all our (>1000) R exercisesFind an R course using our R Course Finder directory
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This is my first article in a two-part series introducing stock data analysis using R.
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