Tag: data science

Feed: R-bloggers. Author: rOpenSci - open tools for open science. pubchunks is a package grown out of the fulltext package. fulltextprovides a single interface to many sources of full text scholarly articles. Aspart of the user flow in fulltext there is an extraction step where fulltext::chunks()pulls parts of articles out of XML format article files. As part of making fulltext more maintainable and focused on simply fetching articles,and realizing that pulling out bits of structured XML files is a more general problem,we broke out pubchunks into a separate package. fulltext::ft_chunks() andfulltext::ft_tabularize() will eventually be removed and we’ll point users topubchunks ... Read More

Feed: IBM Big Data & Analytics Hub - All Content; Author: paul-rivot; The Hadoop landscape looks a little different after Cloudera and Hortonworks’ recent announcement of a $5.2 billion merger.According to the Hortonworks press release, “the combination establishes the industry standard for hybrid cloud data management, accelerating customer adoption, community development and partner engagement.” News outlets are already buzzing about the possibilities as seen in this CNBC video.  As with all mergers, it will take time. The merger’s completion is slated for the first quarter of 2019 and, in the interim, the companies will continue to operate as two separate ... Read More

Feed: IBM Big Data & Analytics Hub - All Content; Author: karan-sachdeva; The business that gets there first won’t necessarily win digital and AI game. It will be the one that ingrains digital and AI in its business as much as possible. Starting from applying intelligent data science where it matters most and progressively using it in every aspect of the business. In the modern banking environment, consumers are well informed. They expect intuitive, engaging and informative experiences when they bank. Banks need solutions that can help them delight their customers with personalized experiences, empower their workforce to provide differentiated ... Read More

Feed: R-bloggers. Author: Dr. Shirin Glander. During my stay in London for the m3 conference, I also gave a talk at the R-Ladies London Meetup on Tuesday, October 16th, about one of my favorite topics: Interpretable Deep Learning with R, Keras and LIME. Keras is a high-level open-source deep learning framework that by default works on top of TensorFlow. Keras is minimalistic, efficient and highly flexible because it works with a modular layer system to define, compile and fit neural networks. It has been written in Python but can also be used from within R. Because the underlying backend can ... Read More

Feed: Hortonworks Blog – Hortonworks. Author: Saumitra Buragohain. What is a Data Science and Engineering Platform Apache Spark is one of our most popular workloads- both on-premises and cloud. As we recently announced HDP 3.0.0  (followed by a hardened HDP 3.0.1), we want to introduce the Data Science and Engineering Platform powered by Apache Spark. As noted in the marketecture above, our Data Science & Engineering Platform is powered by Apache Spark with Apache Zeppelin notebooks to enable Batch, Machine Learning, and Streaming use cases, by personas such as Data Engineers, Data Scientists and Business Analysts. We recently introduced Apache ... Read More

Feed: R-bloggers. Author: aghaynes. I came across this post which gives a method to estimate Pi by using a circle, it’s circumscribed square and (lots of) random points within said square. Booth used Stata to estimate Pi, but here’s some R code to do the same thing… x Note the use of sp and rgeos packages to calculate the intersections. Related R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time ... Read More

Feed: R-bloggers. Author: John Mount. In August of 2003 Thomas Lumley added bquote() to R 1.8.1. This gave R and R users an explicit Lisp-style quasiquotation capability. bquote() and quasiquotation are actually quite powerful. Professor Thomas Lumley should get, and should continue to receive, a lot of credit and thanks for introducing the concept into R. In fact bquote() is already powerful enough to build a version of dplyr 0.5.0 with quasiquotation semantics quite close (from a user perspective) to what is now claimed in tidyeval/rlang. Let’s take a look at that. For our example problem: suppose we wanted to ... Read More

Feed: R-bloggers. Author: David Robinson. I recently came up with the idea for a series of screencasts: I've thought about recording a screencast of an example data analysis in #rstats. I'd do it on a dataset I'm unfamiliar with so that I can show and narrate my live thought process. Any suggestions for interesting datasets to use? — David Robinson (@drob) October 6, 2018 Hadley Wickham had the great suggestion of analyzing a Tidy Tuesday dataset. Tidy Tuesday is a fantastic project run by the R for Data Science online learning community (especially Thomas Mock) that releases an interesting dataset ... Read More

Feed: R-bloggers. Author: Jonathan Carroll. This is the last update to this strange saga… I hope. Image labels… Photo: http://www.premierpaper.com/shop/custom-labels/ Easily two of the most popular posts on my blog are this one and this one describing a couple of ways in which I managed to hack together using an image as a category label in a ggplot. There are likely many people who believe one should never do such a thing, but given the popularity, it seems a lot of people aren’t listening to that. Good on you. via GIPHY One of these posts was recently shared again by ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: William Vorhies. Summary:  Advanced analytics and AI are the fourth great lever available to create organic improvement in corporations.  We’ll describe why this one is different from the first three and why the CEO needs the direct help of data scientists to make this happen.   If you’re a CEO or any other flavor of top executive leading a large company (or if you’re a data scientists trying to help one) then the mission to create continuous improvement is obvious.  Ultimately you probably think about this in terms of EBITDA or ... Read More