Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

Modern Workplace is a monthly thought-leadership webcast series that gives you access to entrepreneurs and thought leaders who are changing the future, brought to you by Microsoft. Join us as we explore cognitive technology, and learn what advances in artificial intelligence will impact analytics and demand for human interaction on the next episode of Modern Workplace, Machine Learning: How technology advances human intelligence, airing April 12th at 8:00 AM PDT / 3:00 PM GMT. This month, two of the industry's most forward thinkers share their predictions of where business is going with big data and how we can take advantage of the changes in technology to come. Gain an insider perspective as we dissect the world of cognitive technology, learn what technological capabilities will be available, and what tasks will still require human input.

In this post, we'll use a supervised machine learning technique called logistic regression to predict delayed flights. But before we proceed, I like to give condolences to the family of the the victims of the Germanwings tragedy. Note: This is a common data set in the machine learning community to test out algorithms and models given it's publicly available and have sizable data. In this blog, we will look at small sample snapsot(2201 flights in January 2004). In another post, we can explore using Big Data technologies such as Hadoop MapReduce or Spark machine learning libraries to do large scale predictive analytics and data mining.

Abstract: In this webinar targeted at developers who are new to Machine Learning, I'll present the type of predictive features that can be integrated in any app (mobile, desktop, web…) and powered by data and machine learning. We'll also look at what's at stake when using ML in production and what the steps are to integrate this technology into real-world apps. In particular, we'll review open source libraries and cloud platforms that make it easier to create and experiment with ML models, but also to deploy them to production. I'll demo how to create a simple predictive model in Python with scikit-learn, how to deploy it as a REST API, and how to use that API. About your host: Louis Dorard is General Chair of the PAPIs.io Louis is also the instructor of the Operational Machine Learning workshop.

There are not many books on deep learning at the moment because it is such a young area of study. There are a few books available though and some very interesting books in the pipeline that you can purchase by early access. In this post you will discover the books available right now on deep learning. Deep Learning Books (I wish) Photo by Indi Samarajiva, some rights reserved. There is a deep learning textbook that has been under development for a few years called simply Deep Learning.

I was wondering if you are aware of any methodology to perform multivariate linear regression on non-standard spaces or domains. I try to reverse-engineer the recipe for the coca cola beverage. The response, Y, is how close my recipe is to the actual formula, based on a number of tastings performed by a number of different people, according to a design of experiment plan. Indeed, it's quite similar to a clinical trial where a mix of atoms or chemical radicals (each combination producing a unique molecule) is tested to optimize a drug. The independent variables are binary, each one representing an ingredient: salt, water, corn syrup etc.

This workshop will attempt to present some of the very recent developments on non-convex analysis and optimization, as reported in diverse research fields: from machine learning and mathematical programming to statistics and theoretical computer science. We believe that this workshop can bring researchers closer, in order to facilitate a discussion regarding why tackling non-convexity is important, where it is found, why non-convex schemes work well in practice and, how we can progress further with interesting research directions and open problems.

Why do we sometimes decide to take risks and other times choose to play it safe? The work is described in the March 21 online early edition of the Proceedings of the National Academy of Sciences. In the study led by John O'Doherty, professor of psychology and director of the Caltech Brain Imaging Center, 24 volunteers repeatedly participated in three types of trials: a "Self" trial, in which the participants were asked to choose between taking a guaranteed 10 or making a risky gamble with a potentially higher payoff; an "Observe" trial, in which the participants observed the risk-taking behavior of a peer (in the trial, this meant a computer algorithm trained to behave like a peer), allowing the participants to learn how often the peer takes a risk; and a "Predict" trial, in which the participants were asked to predict the risk-taking tendencies of an observed peer, earning a cash prize for a correct prediction. Notably in these trials the participants did not observe gamble outcomes, preventing them from further learning about gambles. O'Doherty and his colleagues found that the participants were much more likely to make the gamble for more money in the "Self" trial when they had previously observed a risk-taking peer in the "Observe" trial.

Rembrandt van Rijn was one of the most influential classical painters, and the world lost his amazing talent when he died nearly four centuries ago. And yet his newest masterpiece was unveiled only yesterday. By scanning and analyzing Rembrandt's works, a computer was able to create a new painting in near-perfect mimicry of Rembrandt's style. It has been named, appropriately, 'The Next Rembrandt'. The Next Rembrandt project began when, in October 2014, the Dutch financial institution ING spoke with J. Walter Thompson Amsterdam advertising agency about creating a project that would show innovation in Dutch art.