In this blog post, you'll learn what transfer learning is, what some of its applications are and why it is critical skill as a data scientist. Transfer learning is not a machine learning model or technique; it is rather a'design methodology' within machine learning. Another type of'design methodology' is, for example, active learning. This blog post is the first in a series on transfer learning. You can find the second blog post, which discusses two applications of transfer learning here.

If the fragmented media environment is a sick patient, machine learning may be the cure. That was the proposition Andrew Heyward, visiting scholar from MIT's Media Laboratory and former president of CBS News, outlined in his presentation, "Can Robots Solve Your PR Problems?" at the New York offices of agency Makovsky on Feb. 6. Heyward and his colleagues at MIT Media Lab's Laboratory for Social Machines are studying artificial intelligence solutions to modern plights of the PR practitioner: fake news, polarization, the public's lack of faith in journalism and short attention spans, to name a few. Heyward's group uses machine learning algorithms as their primary tool to map and track the overall health of the public sphere. And soon, PR pros may be able to use those AI insights to make better decisions--whether they're managing a crisis or planning a national campaign. Here are four PR applications of AI and machine learning shared by Heyward.

DeepMind's artificial intelligence programme AlphaZero became the most formidable chess player in the world in December after just four hours of playing the game. DeepMind has also scored off the charts at Go and Shogi, the Asian board games, as well as video games such as Pong and Space Invaders. Machines can now diagnose cancer from tissue slides better than human epidemiologists, translate text from one language to another almost instantly, drive cars, and -- in certain circumstances -- predict social unrest. Even so-called AI pessimists accept that machines will increasingly transform our economy, our lives and our planet. And yet there is one thing that machines cannot yet do, at least not very well: play most sports.…

The quest to give machines a mind of their own occupied the brightest AI specialists in 2017. Machine learning (and especially the newly hip branch, deep learning) practically delivered all of the most stunning achievements in artificial intelligence so far -- from systems that beat us at our own games to art-producing neural networks that rival human creativity. At the onset and in hindsight, experts have heralded 2017 as "The Year of AI". Following its stunning win over the best human Go player in 2016, AlphaGo was upgraded a year later into a generalized and more powerful incarnation, AlphaZero. Free of any human guidance except the basic game rules, AlphaZero learned how to play master-level chess by itself in just four hours.

News of a specialized computer program beating human champions at games like chess and Go might not surprise people as much as it might have before, as it did when Deep Blue beat world chess champ Garry Kasparov back in 1997, or even more recently when Google DeepMind's AI AlphaGo beat Lee Sedol in a stunning upset back in 2016. But the goal for AI researchers has always been to develop an artificial general intelligence (AGI) that's capable at not only merely mastering games, but also learning and solving all kinds of things in a general way, as humans do. And it seems that Google's subsidiary DeepMind has once again gotten one step closer to this goal with AlphaZero, their latest AI development. Their recently published pre-print research outlined how AlphaZero succeeded in handily beating one of the world's top chess engines -- after teaching itself and mastering the game in four hours and reaching a "superhuman" level of play in a mere 24 hours in not only chess but in two other different types of board games. The most remarkable thing about this latest evolution is that in contrast to finely hand-tuned game-playing programs, the only input AlphaZero had were the basic rules of the game.

For many good reasons, much of the highest quality machine learning educational resources tend to have a very strong focus on theory, especially at the beginning. There seems, however, to be an increasing trend of getting on to the practical from the start, and mixing practice and theory along the way as resources progress. This post presents 5 such resources. Covering machine learning right from basics, as well as coding algorithms from scratch and using particular deep learning frameworks, these resources cover quite a bit of ground. They are also all free, so get reading, get watching, and get coding.

The Pentagon's new #AI is already hunting terrorists. Just a couple of the many ways #Deep-learning will add value to every enterprise. Signal: Is the US losing Latin America?

Finding cats and dogs in pictures using deep learning is easy! Finding tumors and lesion in the brain using deep learning is harder, but we are getting there. When planning the treatment and tracking the progression of various brain diseases, locating the exact regions affected is important. Consider the case of brain tumors. When deciding whether or not to perform surgery it is crucial to know exactly where the tumor is located.

Pathology is on the verge of a revolution from a qualitative to a quantitative discipline. The PAIGE AI is trained by the world's foremost cancer experts on tens of thousands of digital slides. Artificial Intelligence is the core of PAIGE. Our team of Machine Learning experts has a decade of experience in building large scale ML systems for Computational Pathology. We develop novel deep learning and ensemble models to create the first clinical-grade AI in pathology.

Are you thinking what I'm thinking? It's a question researchers have been asking artificial intelligence from the start. Now, a team at Google's DeepMind has developed a virtual 3D laboratory called Psychlab in which both humans and machines can take a range of simple tests and compare their cognitive abilities.