Tag: GitHub

Feed: R-bloggers. Author: Greg Wilson. We received almost 400 applications for our 2019 internship program from students with very diverse backgrounds. After interviewing several dozen people and making some very difficult decisions, we are pleased to announce that these twelve interns have accepted positions with us for this summer: Therese Anders: Calibrated Peer Review. Prototype tools to conduct experiments to see whether calibrated peer review is a useful and feasible feedback strategy in introductory data science classes and industry workshops. (mentor: Mine Çetinkaya-Rundel) Malcolm Barrett: R Markdown Enhancements. Tidy up and refactoring the R Markdown code base. (mentor: Rich Iannone) ... Read More

Feed: R-bloggers. Author: Tobias Krabel. Introduction At STATWORX, we are not only helping customers find, develop, and implement a suitable data strategy but we also spend some time doing research to improve our own tool stack. This way, we can give back to the open-source community. One special focus of my research lies in tree-based ensemble methods. These algorithms are bread and butter tools in predictive learning and you can find them as a standalone model or as an ingredient to an ensemble in almost every supervised learning Kaggle challenge. Renowned models are Random Forest by Leo Breiman, Extremely Randomized ... Read More

Feed: R-bloggers. Author: Laran Ikal. Introduction: We will identify anomalous products on the production line by using measurements from testing stations and deep learning models. Anomalous products are not failures, these anomalies are products close to the measurement limits, so we can display warnings before the process starts to make failed products and in this way the stations get maintenance.  Before starting we need the next software installed and working: – R language installed.– All the R packages mentioned in the R sources.– Testing stations data, I suggest to go station by station.– H2O open source framework.– Java 8 ( ... Read More

Feed: R-bloggers. Author: Open Analytics. ShinyProxy is a novel, open source platform to deploy Shiny apps for the enterpriseor larger organizations. Secured Embedding of Shiny Apps Since version 2.0.1 ShinyProxy provides a REST API to manage (launch, shut down) Shiny apps and consume the content programmatically inside broader web applications or portals. This allows to cleanly separate the responsiblity for the Shiny apps (data science teams) and those broader applications (IT teams) while still achieving seamless integration between the two from the user’s perspective. With this release we go one step further and support the industry standard to protect REST ... Read More

Feed: R-bloggers. Author: John Mount. With all of the excitement surrounding cdata style control table based data transforms (the cdata ideas being named as the “replacements” for tidyr‘s current methodology, by the tidyr authors themselves!) I thought I would take a moment to describe how they work. cdata defines two primary data manipulation operators: rowrecs_to_blocks() and blocks_to_rowrecs(). These are the fundamental transforms that convert between data representations. The two representations it converts between are: A world where all facts about an instance or record are in a single row (“rowrecs”). A world where all facts about an instance or record ... Read More

Feed: R-bloggers. Author: Peter Prevos. The post Decode Lyrics in Pop Music: Visualise Prose with the Songsim algorithm appeared first on The Lucid Manager. Music is an inherently mathematical form of art. Ancient Greek mathematician Pythagoras was the first to describe the logic of the scales that form melody and harmony. Numbers can also represent the rhythm of the music. Even the lyrics have a mathematical structure. Poets structure syllables and repeat words to create pleasing sounding prose. This article shows how to decode lyrics from pop songs and visualise them using the Songsim method to analyse their metre. Decode ... Read More

Feed: R-bloggers. Author: Super User. Doing human face detection with computer vision is probably something you do once unless you work for police departments, you work in the surveillance industry or for the Chinese government. In order to reduce the time you lose on that small exercise, bnosac created a small R package (source code available at https://github.com/bnosac/image) which wraps the weights of a Single Shot Detector (SSD) Convolutional Neural Network which was trained with the Caffe Deep Learning kit. That network allows to detect human faces in images. An example is shown below (tested on Windows and Linux). install.packages("magick")install.packages("image.libfacedetection", ... Read More

Feed: AWS Partner Network (APN) Blog. Author: Sagar Khasnis. By Sagar Khasnis, Partner Solutions Architect at AWSBy Awaneendra Tiwari, Cloud Architect at BrillioSome of the customers we work with have a central database where they keep tag values, and they want to enforce tags at provisioning using the tag enforcement capability of AWS Service Catalog. For example, a customer can have a central location where they keep all of their constantly-updated cost center information, and they use that information as tag values in their AWS Service Catalog portfolios. In this post, we’ll show you how to implement tag options so the ... Read More

Feed: SAS Blogs. Author: Neela Niranjani Vengateshwaran. Computer vision is one of the most sought-after artificial intelligence (AI) applications today, finding a wide variety of use cases in image recognition, object detection, biomedical assessment, and more. SAS supports a diverse set of AI and deep learning capabilities that can be used in many of these applications. One of them is our support for object detection using the popular You Only Look Once (YOLO) algorithm. YOLO algorithms are popular for identifying common objects that can be quickly recognized in a single glance. This blog post is aimed at creating a good ... Read More

Feed: Microsoft Azure Blog. Author: Harini Gupta. A few months ago, I shared best practices for alerting on metrics with Azure Database for PostgreSQL. Though I was able to cover how to monitor certain key metrics on Azure Database for PostgreSQL, I did not cover how to monitor and alert on the performance of queries that your application is heavily relying on. As a PostgreSQL database, from time to time you will need to investigate if there are any queries running indefinitely on a PostgreSQL database. These long running queries may interfere with the overall database performance and likely get ... Read More