From our blog

You can browse our list of posts that describe previous and future presentations.

Cancelled: From Data to Dashboards in a Day

on March 14, 2020

Details Sign up on Eventbrite not Meetup https://www.eventbrite.com/e/95552487061/ Overview From data to dashboards in a day. Learn the art and science of developing interesting, informative, and interactive dashboard in today’s most popular analytics and visualization tool Tableau. This workshop will discuss the workflow, tools, and design concepts you need to create engaging dashboard reports. The design of a dashboard can be the difference between a dashboard that is hardly used versus one that becomes a popular tool of decision-makers.

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Power BI and March Madness

on March 7, 2020

Details Introduction Power BI is a business analytics solution that lets you visualize data, share insights, or embed them in an app or website. It allows easy access to connect to hundreds of data sources, create dashboards and reports. Power BI, can run R scripts and create data models and visualizations. Suresh will give a demo on how you can use your R stills to interact with Power BI.

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Book Club: Feature Engineering and Selection

on February 26, 2020

Details After the success of our first book club, we are looking to start a new one. Again this will be headed up by Xi Chen. The idea is to motivate us to read books and discussing them together. This will help all of us to develop our skills. The format will be that the leader will prepare a short summary of the material and present it to the group. We will then discuss the material and do some exercises.

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reticulate: R Interface to Python

on January 28, 2020

Details Bring your laptop Introduction This month this we are going to try something new and break from our traditional two talks. Michael Espero is going to introduce the ‘reticulate’ package. Reticulate provides a comprehensive set of tools for interoperability between Python and R. The package includes facilities for: Calling Python from R in a variety of ways including R Markdown, sourcing Python scripts, importing Python modules, and using Python interactively within an R session.

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