— In the News —
Hyper-realistic computer games may offer an efficient way to teach AI algorithms about the real world.
Cautionary tales about data gaps and assumptions.
Nobody understands why deep neural networks are so good at solving complex problems. Now physicists say the secret is buried in the laws of physics.
— Sponsored Link —
IEEE BigData, the Business-Higher Education Forum, and IBM are partnering to host a one-day workshop on Sunday, October 23, just before the start of the IBM World of Watson conference. This workshop is suited for academics who are responsible for artificial intelligence, machine learning, cognitive science, citizen analyst, data science, or data engineering curriculum and programs.
How will these emerging fields evolve?
What competencies will every student require?
What competencies will specialists require?
What competencies will business expect students acquire?
Join the conversation on October 23rd.
— Tools and Techniques —
A "mostly complete chart of architectures." Both the diagrams and descriptions are fantastic and are easy to follow.
Teaching analytics through football. Great article.
Interested in machine learning but not sure where to start? Here's how one developer went from being a complete novice to using it professionally in a year. If you're interested in this topic, the Hacker News thread is also worthwhile.
Quora Q/A with DJ Patil, the U.S. Chief Data Scientist. Questions cover a broad range of topics including recommended tools, languages, and projects he's been involved with at the White House.
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
— Resources —
O'Reilly Media has made a large collection of their data-related ebooks available for free. There's a lot here, including topics in analytics, AI, big data, architecture, industry reports, etc.
— Data Viz —