2017

Citibike Business Opportunity: Advertising

October 15, 2017 | Josh Yoon

Introduction It is hard to wander around New York City without seeing rows of dozens of bright blue Citibikes planted in the middle of busiest nooks […] The post Citibike Business Opportunity: Advertising appeared first on NYC Data Science Academy Blog.
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Citibike Business Opportunity: Advertising

October 15, 2017 | Josh Yoon

Introduction It is hard to wander around New York City without seeing rows of dozens of bright blue Citibikes planted in the middle of busiest nooks […] The post Citibike Business Opportunity: Advertising appeared first on NYC Data Science Academy Blog. [Read more...]

Barplot with ggplot2/plotly

October 15, 2017 | rdata.lu Blog | Data science with R

Hello everyones, I just finished my MOOC on Foundations of strategic business analitycs. It was interresting and at the end of this course, I had to present a graph that was suppose to be relevent for a business organization. Different datasets were availables: speed dating, Co2 emissons, bike sharing, loans, ... [Read more...]

Why Use Docker with R? A DevOps Perspective

October 15, 2017 | Jeroen Ooms

There have been several blog posts going around about why one would use Docker with R. In this post I’ll try to add a DevOps point of view and explain how containerizing R is used in the context of the OpenCPU system for building and deploying R servers. Has ...
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Rats in NYC! A Retrospective

October 15, 2017 | Ben Brunson

32 million dollars. Take a while, let that sink in. Thirty-two. Million. Dollars. Three months ago, mayor de Blasio presented a $32 million dollar plan to […] The post Rats in NYC! A Retrospective appeared first on NYC Data Science Academy Blog.
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Rats in NYC! A Retrospective

October 15, 2017 | Ben Brunson

32 million dollars. Take a while, let that sink in. Thirty-two. Million. Dollars. Three months ago, mayor de Blasio presented a $32 million dollar plan to […] The post Rats in NYC! A Retrospective appeared first on NYC Data Science Academy Blog.
[Read more...]

Running R Code in Parallel

October 14, 2017 | Andrew Treadway

Background Running R code in parallel can be very useful in speeding up performance. Basically, parallelization allows you to run multiple processes in your code simultaneously, rather than than iterating over a list one element at a time, or running a single process at a time. Thankfully, running R code ...
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Creating interactive SVG tables in R

October 14, 2017 | Riddhiman

In this post we will explore how to make SVG tables in R using plotly. The tables are visually appealing and can be modified on the fly using simple drag and drop. Make sure you install the latest version of Plotly i.e. v 4.7.1.9 from Github using devtools::install_github("...
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An AI pitches startup ideas

October 13, 2017 | David Smith

Take a look at this list of 13 hot startups, from a list compiled by Alex Bresler. Perhaps one of them is the next Juicero? FAR ATHERA: A CLINICAL AI PLATFORM THAT CAN BE ACCESSED ON DEMAND. ZAPSY: TRY-AT-HOME SERVICE FOR CONSUMER ELECTRONICS. MADESS: ON-DEMAND ACCESS TO CLEAN WATER. DEERG: AI ... [Read more...]

Uber assignment with lpSolve

October 13, 2017 | insightr

By Yuri Fonseca In this post we are going to make an Uber assignment simulation and calculate some metrics of waiting time through simulation. Setting Suppose we live in a 100×100 block city where each block takes 1 minute to … Continue reading →
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.rprofile: David Smith

October 13, 2017 | Kelly O'Briant

In this occasional series, we interview someone using a loosely defined set of interview questions for the purpose of “Demystifying the Creative/Development Process of the R Community”. This interview was conducted and prepared by Kelly O'Briant as part of an rOpenSci unconf17 project. David Smith is a Blogger and ... [Read more...]

Practical Machine Learning with R and Python – Part 2

October 12, 2017 | Tinniam V Ganesh

In this 2nd part of the series “Practical Machine Learning with R and Python – Part 2”, I continue where I left off in my first post Practical Machine Learning with R and Python – Part 2. In this post I cover the some classification algorithmns and cross validation. Specifically I touch -Logistic Regression ...
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