Tag: data scientist

Feed: R-bloggers. Author: Learning Machines. The two most disruptive political events of the last few years are undoubtedly the Brexit referendum to leave the European Union and the election of Donald Trump. Both are commonly associated with the political consulting firm Cambridge Analytica and a technique known as Microtargeting. If you want to understand the data science behind the Cambridge Analytica/Facebook data scandal and Microtargeting (i.e. LASSO regression) by building a toy example in R read on! The following post is mainly based on the excellent case study “Cambridge Analytica: Rise and Fall” by my colleague Professor Oliver Gassmann (who ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: William Vorhies. Summary:  Here’ a proposal for real ‘zero touch’, ‘set-em-and-forget-em’ machine learning from the researchers at Amazon.  If you have an environment as fast changing as e-retail and a huge number of models matching buyers and products you could achieve real cost savings and revenue increases by making the refresh cycle faster and more accurate with automation.  This capability likely will be coming soon to your favorite AML platform. Is there a future in which we can really ‘set-em-and-forget-em’ machine learning?  So far Automated Machine Learning (AML) is delivering on ... Read More

Feed: R-bloggers. Author: Lukas Feick. Cross-validation is a widely used technique to assess the generalization performance of a machine learning model. Here at STATWORX, we often discuss performance metrics and how to incorporate them efficiently in our data science workflow. In this blog post, I will introduce the basics of cross-validation, provide guidelines to tweak its parameters, and illustrate how to build it from scratch in an efficient way. Model evaluation and cross-validation basics Cross-validation is a model evaluation technique. The central intuition behind model evaluation is to figure out if the trained model is generalizable, that is, whether the ... Read More

Feed: R-bloggers. Author: Samantha Toet. [This article was first published on RStudio Blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. We’re hosting a free, half-day event with one of our Full Service Certified Partners, ProCogia, in Seattle on Wednesday October 9th. This event is for data science and IT teams that want to learn more about: helpful new RStudio R packages like pins what RStudio professional products can do for your data ... Read More

Feed: R-bloggers. Author: R Views. [This article was first published on R Views, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. In the first article of this series, we looked at understanding type I and type II errors in the context of an A/B test, and highlighted the issue of “peeking”. In the second, we illustrated a way to calculate always-valid p-values that were immune to peeking. We will now explore multiple hypothesis ... Read More

Feed: R-bloggers. Author: Alexander Landa. [This article was first published on R-posts.com, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Go HERE to learn more about the ODSC West 2019 conference with a 20% discount! (or use the code: ODSCRBloggers) At this point, most of us know the basics of using and deploying R—maybe you took a class on it, maybe you participated in a hackathon. That’s all important (and we have tracks ... Read More

Feed: R-bloggers. Author: Elisa Gladu. [This article was first published on RStudio Blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Join RStudio at one of our Fall and Winter workshops! We’ll be hosting a few different workshops in a variety of cities across the US and UK. Topics range from building tidy tools, to teaching data science, to mastering machine learning. See below for more details on each workshop and how to ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: ajit jaokar. Introduction Co-relation does not equal causation – is a mantra drilled into a Data Scientist from an early age That’s fine .. But very few talk of the follow-on question .. How exactly do you determine causation? This problem is further compounded because most books and examples are based on standard datasets (ex: Boston, Iris etc) . These examples do not discuss causation because the features chosen are already determined to be causal (ex the factors affecting house prices are chosen to be causal) So, if we start from ... Read More

Feed: Big Data Made Simple. Author: Andrej Kovačević. Right now, the need for a wholesale upgrade of the way businesses handle data security has never been more obvious. With each passing day, the threats to that data will grow and become an even bigger source of risk. One need only look at the companies who’ve fallen victim to data breaches in recent months to understand the scope of the problem.The thing that’s holding some businesses back, though, is that their data systems are so sprawling that it’s hard to protect everything in real-time. That’s causing many businesses to make large ... Read More

Feed: R-bloggers. Author: Posts on Data Science Diarist. Reddit is a popular website for opinion sharing and news aggregation. The site consists of thousands of user-made forums, called subreddits, which cover a broad range of subjects, including politics, sports, technology, personal hobbies, and self-improvement. Given that most Reddit users contribute to multiple subreddits, one might think of Reddit as being organized into many overlapping communities. Moreover, one might understand the connections among these communities as making up a kind of social structure. Uncovering a population’s social structure is useful because it tells us something about that population’s identity. In the ... Read More