< 1 min. read Need a quick reference when studying probability? Here’s a cheatsheet by William Chen and Joe Blitzstein for reference.
< 1 min. read In this resource page RStudio provides various cheatsheets for various packages that is very useful for doing data science in the R environment including data wrangling, visualization and package development.
< 1 min. read JJ Allaire from RStudio wrote a step-by-step guide on how to configure secured downloads of R packages. Secured downloading of R packages (via HTTPS connection) ensures that you get your packages from legitimate, trusted sources.
< 1 min. read If you have used R’s read.csv function, you will inevitably use the stringsAsFactors=FALSE option. Roger Peng offers a brief history into why the default for stringAsFactors option is TRUE. Alternatively, you can use the read_csv function from the readr package by Hadley Wickham, which does not automatically convert characters to factors.
< 1 min. read Wonder which GRC or SMC you are in? Here’s a visualization that has been circulating around for your reference.
< 1 min. read Watch the show Perspectives – From Big Data to Smart Data on Channel NewsAsia Online for insights from industry leaders and academia on Big Data, it’s usage and its effects on individuals and companies.
< 1 min. read This site created by Sean McClure, data scientist at ThoughtWorks, shows an overview of data science concepts. I find this structured approach very useful as a gauge to discover areas of improvement. It also serves to provide more information via Wikipedia links at the terminal nodes.
< 1 min. read On the journey of Data Science, you will probably come across Calculus. For students and working professionals alike, the availability of cheat sheets make lives easier. I’m happy and grateful to find out that the Calculus cheat sheets I’ve referred to during my university days are still available on the net, thanks to Paul Dawkins […]
< 1 min. read Resource Link The lecturers of the JHU Data Science Specialization courses have created a Github repository of resources for students of the courses. If you are interested in Data Science, hope these resources are useful to you too.