Charles River Analytics: Software Engineer I – Intelligent Systems

[unable to retrieve full-text content]Seeking an enthusiastic Software Engineer to design and develop cutting-edge intelligent systems applied to areas such as intelligent tutoring, serious games, crowdsourcing, and skill modeling and assessment.
Original Post: Charles River Analytics: Software Engineer I – Intelligent Systems

Charles River Analytics: Software Engineer III – Cesium.js Developer

[unable to retrieve full-text content]Seeking an experienced Cesium.js developer to join a top-notch team of software engineers and data scientists developing web-based solutions for both DoD and commercial customers.
Original Post: Charles River Analytics: Software Engineer III – Cesium.js Developer

Just use a scatterplot. Also, Sydney sprawls.

Dual-axes at tipping-point Sydney’s congestion at ‘tipping point’ blares the headline and to illustrate, an interactive chart with bars for city population densities, points for commute times and of course, dual-axes. Yuck. OK, I guess it does show that Sydney is one of three cities that are low density, but have comparable average commute times to higher-density cities. But if you’re plotting commute time versus population density…doesn’t a different kind of chart come to mind first? y versus x. C’mon. Let’s explore. First: do we even believe the numbers? Comments on the article point out that the population density for Phoenix was corrected after publication, and question the precise meaning of city area. Hovering over the graphic to obtain the values, then visiting Wikipedia’s city pages, we can create a Google spreadsheet which I hope is publicly-visible at this link.…
Original Post: Just use a scatterplot. Also, Sydney sprawls.

Charles River Analytics: Software Engineer – Human Machine Interface Design

[unable to retrieve full-text content]Seeking a Software Engineer to work closely with small teams of scientists, software engineers, and subject matter experts, using modern technologies, to design and develop cutting edge information visualizations, human automation teaming methodologies, and novel display interfaces.
Original Post: Charles River Analytics: Software Engineer – Human Machine Interface Design

Crawling the internet: data science within a large engineering system

by BILL RICHOUX Critical decisions are being made continuously within large software systems. Often such decisions are the responsibility of a separate machine learning (ML) system. But there are instances when having a separate ML system is not ideal. In this blog post we describe one of these instances — Google search deciding when to check if web pages have changed. Through this example, we discuss some of the special considerations impacting a data scientist when designing solutions to improve decision-making deep within software infrastructure.Data scientists promote principled decision-making following several different arrangements. In some cases, data scientists provide executive level guidance, reporting insights and trends. Alternatively, guidance and insight may be delivered below the executive level to product managers and engineering leads, directing product feature development via metrics and A/B experiments.This post focuses on an even lower-level pattern, when…
Original Post: Crawling the internet: data science within a large engineering system

Video: R for AI, and the Not Hotdog workshop

Related To leave a comment for the author, please follow the link and comment on their blog: Revolutions. 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 series, trading) and more… If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook…
Original Post: Video: R for AI, and the Not Hotdog workshop