Tony Ojeda

In this first week of 2013, we found a variety of interesting data science articles ranging in topics from some ways to get started in data science and some interview questions you can expect if you land an interview to some future applications for machine-generated data.

In this week’s round-up:

• Software engineer’s guide to getting started with data science
• Interview Questions for Data Scientists
• General Electric lays out big plans for big data
• Early Evidence Is Often Too Early And Not Really Evidence
• Scientists construct first map of how the brain organizes everything we see

Check out the round-up!

(Source: datacommunitydc.org)

This week, we encountered several interesting data articles and blog posts we thought were worthwhile for the round-up. As this year comes to a close, we were reminded of how much noise is out there about data, having to sift through hundreds of “Year in Review” and “Big Data Predictions for 2013″ articles that are currently being published. We chose to bypass those for this round-up in favor of focusing on longer term trends, interesting ways data is being used, and important things to consider when handling data.

Happy New Year, everyone!

In this week’s round-up:

• We don’t need more data scientists, just make big data easier to use
• The Secret Life of Data in the Year 2020
• Open data is not a panacea
• The Danger Of Big Data
• How Missile Tracking Cameras Are Remaking The NBA

Check out the round-up!

For this week’s round-up of the most interesting data articles and blog posts from around the web, we have several articles ranging in topics from using big data in small and medium sized businesses to using machine learning to combat bullying.

In this week’s round-up:

• So I’ve got Big Data. Now What?
• How small and mid-sized businesses can tap the power of big data
• The key to data science? Telling stories
• Fighting bullying with machine learning

Read the round-up!

(Source: datacommunitydc.org)

Some companies are increasingly closing their APIs and locking down their data with the aim of figuring out how to monetize it. The government, however, is doing the opposite. It’s actively creating API’s to make government more transparent and accessible.

This is creating new opportunities for businesses who are willing to make sense of and transform the data into something valuable for a particular market. These new opportunities and the lessons learned by those in the trenches was the theme for Data Business DC‘s (DBDC’s) second meetup Money For Nothing — Productizing Government Data. Presenters ranged from the small, one-person startup using government data as the foundation of the business to a senior government official talking about the challenges, successes, and opportunities of using government data.

Check out the review!

(Source: datacommunitydc.org)

This past week was an exciting one in data. There were a lot of good articles published and we found several of them interesting enough to include in this week’s round-up.

In this week’s round-up:

• Kurzweil joins Google
• Big Data’s Biggest Obstacles
• Operations, machine learning and premature babies
• How To Augment Predictive Analytics with Human Intelligence
• Define your big data strategy with these key steps

(Source: datacommunitydc.org)

This past weekend, five intrepid souls (Robert Vesco, Valerie Coffman, Harlan Harris, Octavian Geagla, Sean Patrick Murphy) from Data Community DC converged on New York City for the first Hack//Meat.

This week, we continue our data round-up series containing the most interesting data science, machine learning, statistics, and analytics articles we’ve come across.  We found several great articles this week with topics spanning from big data to business intelligence with some interesting data visualizations sprinkled in there.

In this week’s round-up:

• What a Big Data Business Model Looks Like
• Mapping Twitter’s Python and Data Science Communities
• Big Data Leader Cloudera Raises $65M to Fuel Further Hadoop Adoption
• Infographic: Google’s Flu Map Might Predict the Next Big Epidemic
• Top 10 Trends for Business Intelligence

(Source: datacommunitydc.org)