This post highlights a number of important applications found for deep learning so far. It is well known that 80% of data is unstructured. Unstructured data is the messy stuff every quantitative analyst tries to traditionally stay away from. It can include images of accidents, text notes of loss adjusters, social media comments, claim documents and review of medical doctors etc. Unstructured data has massive potential but has never been traditionally considered as a source of insight before. Deep Learning is becoming the method of choice for its exceptional accuracy and capturing capacity for unstructured data.

Nobel economics laureate and psychologist Daniel Kahneman -- considered the father of behavioral economics – retired from his teaching position at Princeton a few years ago to co-found a consulting firm in New York. In a talk at the recent Wharton People Analytics Conference, he said of his consulting experience that he had "expected to be awed" by the quality of the decision-making in organizations "that need to make profits to survive in a competitive world." "You look at large organizations that are supposed to be optimal, rational. And the amount of folly in the way these places are run, the stupid procedures that they have, the really, really poor thinking you see all around you, is actually fairly troubling," he said, noting that there is much that could be improved. Figuring out how to make the act of decision-making "commensurate with the complexity and importance of the stakes" is a huge problem, in Kahneman's view, to which the business world does not devote much thought.

Gamification is all the rage these days. In order to distill this down to something simple was the task at hand. Here are the briefly highlights after reviewing more than 100 documents, articles and reports. Since people and management hate training, there is a new way to accomplish training, customer acquisition, corrective behavior and other staff behavior and customer participation issues. The game designer sets the goals, rewards (hard dollars and soft benefits such as recognition, etc.) management, legal and outcome.

This has been one of the most intriguing questions in science fiction and philosophy since the advent of machines. With modern technology, such questions are no longer bound to creative conjecture. Machine learning is all around us. From deciding which movie you might want to watch next on Netflix to predicting stock market trends, machine learning has a profound impact on how data is understood in the modern era. This tutorial aims to give you an accessible introduction on how to use machine learning techniques for your projects and data sets. In just 20 minutes, you will learn how to use Python to apply different machine learning techniques -- from decision trees to deep neural networks -- to a sample data set.

Top Machine Learning & Data Mining Books - in this post, we have scraped various signals (e.g. We have combined all signals to compute the Quality Score for each book and publish the list of top Machine Learning and Data Mining books. The readers will love the list because it is data-driven & objective. This book is very well rated on Amazon website and is written by three professors from USC, Stanford and University of Washington. The book's authors: Gareth James, Daniela Witten, Trevor Hastie, & Rob Tibshirani all have backgrounds in statistics.

Platform-based talent markets help put the emphasis in human-capital management back where it belongs--on humans. The best way to organize corporations--it's a perennial debate. But the discussion is becoming more urgent as digital technology begins to penetrate the labor force. Although consumers have largely gone digital, the digitization of jobs, and of the tasks and activities within them, is still in the early stages, according to a recent study by McKinsey Global Institute (MGI). Even companies and industries at the forefront of digital spending and usage have yet to digitize the workforce fully (Exhibit 1).1 1.See McKinsey Global Institute, "Digital America: A tale of the haves and have-mores," December 2015. The stage is set for sweeping change as artificial intelligence, after years of hype and debate, brings workplace automation not just to physically intensive roles and repetitive routines but also to a wide range of other tasks. MGI estimates that roughly up to 45 percent of the activities employees perform can be automated by adapting currently demonstrated technologies.

"With artificial intelligence, we are summoning the demon," chief executive of Tesla and Space X Elon Musk eerily warned listeners at the MIT Aeronautics and Astronautics department's Centennial Symposium in October of 2014. "In all those stories where there's the guy with the pentagram and the holy water, it's like, yeah he's sure he can control the demon. Some people believe artificial intelligence is evil and will end the human race while others believe they will only enhance our well-being. The thought of an evil robot stampeding through a mound of human skulls are deeply ingrained by way of modern pop culture and movies like James Cameron's iconic Terminator. These outrageous, though plausible, thoughts make the idea of artificial intelligence less attractive when giving a helping hand to everything in your everyday life. Someone that truly understood the beginnings of A.I. was the brilliant yet tragic Alan Turing. He was an English scientist who broke the Nazi Enigma Machine's code and helped bring WWII to an end. Turning made many predictions about artificial intelligence, his lesser known yet most significant warns about AI's future threat. In 1951 he wrote, "At some stage… we should have to expect the machines to take control.

As the country reels from the spasm of gun violence that killed two black men and five police officers this week, a prominent digital vigilante is using an online tool he hacked together to keep an eye on hot spots that seem at risk of boiling over into bloodshed. The Web app, which is powered partly by artificial intelligence, analyzes posts on social media as well as police radio chatter and feeds of the local airspace in virtually any region. To detect rumblings of unrest and alert the public. At the moment, the tool has its gaze trained on Baton Rouge, where protesters backed by the New Black Panther Party have gathered for a rally. "I'm looking for any indication they are coordinating skirmishes. Using IBM's Watson AI, the tool not only examines large collections of tweets but -- somewhat eerily -- also can go through a single user's timeline and, with Watson's machine learning technology, offer an analysis of that user's "trustworthiness, propensity toward violence [and] openness," the Jester said. That information, he said, could hold clues to a criminal's intentions. If the Jester's name sounds familiar, that's because the hacker has appeared elsewhere -- on Time's list of most influential Internet personalities, on CNN and, according to a recent blog post, on an upcoming episode of USA's "Mr.

Forget your smartphones and other accessories: voice communication underpinned by artificial intelligence (AI) is going to be the basis for our connected day-to-day lives. And the shift has already begun! Some pointers: a recent survey, which polled a representative sample of 500 US residents, revealed that only 2% of iPhone users have never used the virtual assistant Siri. Meanwhile Google revealed during the Google IO developer festival held in Mountain View in May just how much emphasis the Internet giant is now placing on voice technology. In the very near future, voice might well be used to direct Google searches, a prospect which could explain the firm's massive investment in Google Assistant. Another pointer: we can count on seeing increasingly high-performance and lower-cost artificial intelligence tools.

The headline isn't mine – it was from Bloomberg (I think'robots' sell). The article is really talking about online dispute resolution tools powered by artificial intelligence. Most people are familiar with this kind of tool primarily because of eBay. Its site has an automated dispute-resolution tool which settles 60 million claims every year. Now, some countries are deploying similar technology to let people negotiate divorces, landlord-tenant disputes, and other legal conflicts.