This Week in Data Science (August 23, 2016)

Here’s this week’s news in Data Science and Big Data.

Don’t forget to subscribe if you find this useful!

Interesting Data Science Articles and News

• This is What It Takes To Connect a Volcano to the Internet – Explorers, volcanologists, GE, and the Nicaraguan government have banded together to bring the Masaya volcano in Nicaragua into the 21st century, by installing sensors that can compile huge amounts of data.
• Uber’s First Self-Driving Fleet Arrives in Pittsburgh This Month – Starting later this month, Uber will allow customers in downtown Pittsburgh to summon self-driving cars from their phones. Uber will be the first company to bring a self-driving car-sharing service to market.
• Why You Should Embrace Analytic Athleticism – Focus on hiring the right people who have a strong level of analytic athleticism. Just as good athletes can spot one another, so can people who are good at analytics.
• Five great charts in 5 lines of R code each – Journalist, Sharon Machlis, displays how useful R is for data viualization with these five charts.
• Sprinters Should Start Fast; Everyone Else Should Finish Fast – Data visualization charts are used to analyze the best pacing technique for runners.
• Why the Future of the Olympics are “The Internet of Olympic Games” – Francisco Maroto, a Telco Industry Executive, discusses the impact of IoT on the Olympic Games in Rio.
• Think It’s Hot Now? Just Wait – July wasn’t just hot – it was the hottest month ever recorded, according to NASA. And this year is likely to be the hottest year on record.
• New R extension gives data scientists quick access to IBM’s Watson – Aiming to put IBM’s Watson AI within closer reach, analytics firm Columbus Collaboratory recently released a new open-source R extension called CognizeR.
• Will Smart Machines Be Less Biased Than Humans? – Some critics claim that smart machines will have systemic “algorithmic bias” that enables government and corporate abuse.
• The 10 Algorithms Machine Learning Engineers Need to Know – Read this introductory list of contemporary machine learning algorithms of importance that every engineer should understand.
• Use Big Data to Create Value for Customers, Not Just Target Them – To build lasting advantage, marketing programs that leverage big data need to turn to more strategic questions about longer term customer stickiness, loyalty, and relationships.
• From Now On You’ll Be Able to Access NASA Research for Free – NASA has announced that it will now provide public access to all journal articles on research funded by the agency.
• New Brain-Mapping Technique Captures Every Connection Between Neurons –
• A Beginner’s Guide to Neural Networks with R! – A new technique called MAP-seq uses RNA bar codes to quickly and cheaply chart connections between brain cells.
• Forget Python vs. R: how they can work together – Learn how employees at Civis use both R and Python for their work.

Upcoming Data Science Events

• Constant Contact: Using IBM BigInsights to Create Business Insight – Join this session on August 25th to learn how Constant Contact, a leader in email marketing, is using IBM BigInsights to create useful insights for their clients in a way that scales.
• IBM i2 Summit – Join the IBM i2 Summit on August 30-31 to hear directly from experts who are using all forms of data, including “dark data,” to outthink threats.
• Combining IBM SPSS Statistics and R for competitive advantage – This Data Science Central Webinar event on September 1st, will show you how SPSS Statistics can help you keep up with the influx of new data and make faster, better business decisions without coding.
• Big Data and Health presented by IBM Canada – Join We Are Wearables Toronto and IBM Canada on September 16th for a look at how wearables and sensors are changing healthcare.
• How Data Can Help in the Fight Against Sexual Assault – Join the Center for Data Innovation and Rise, a civil rights nonprofit, on October 6th in Washington D.C., for a panel discussion on how policymakers and law enforcement can develop data-driven policies and practices to help in the fight against sexual assault and improve the lives of survivors.