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Web Scraping for Data Science — Part 2

Click here to learn more about author Steve Miller. Read Part 1 of this blog series here. Between R and Python, analytics pros are covered on most data science bases R-Python. In last month’s blog, I discussed simple webscraping using Python in a Jupyter notebbok, the nifty css-generating tool SelectorGadget, and the Python XML and HTML handling package lxml. […]

The API Economy: A Big Ball of CRUD

Click this link to learn more about the author Dave Duggal. Quote: “The use of APIs has exploded with the growth of distributed computing, driven by the popularity of the Web, Cloud and now, the Internet of Things (IoT)” Back in 1999 an academic paper, “The Big Ball of Mud” exposed fundamental limitations of ‘modern’ software […]

Will Data Scientists Soon Be Obsolete?

by Angela Guess Bernard Marr recently opined in Forbes, “The job of data scientist — the quintessential big data job, and the job that was just voted the best job in America for 2016 — is at risk. Data scientists have been called ‘unicorns’ because finding the right person with the right set of skills […]

UK to Set Up a Council of Data Science Ethics

by Angela Guess Rebecca Bazeley recently wrote in PHG Foundation, “The UK Government is to set up a Council of Data Science Ethics. The development comes in response to recommendations from the Science and Technology Committee’s report The big data dilemma published earlier this year. The Council of Data Science Ethics will be established within […]

A Liberal Arts Approach to Data Science

by Angela Guess George Mount recently wrote in Smart Data Collective, “This week I read a great piece by Adam Weinberg, the president of Denison University, on his school’s initiatives to apply a liberal arts approach to data science. This is shocking to most, but why? Let’s diagram this phrase ‘data science’ (English skills!). Data […]