Deep learning is currently one of the best providers of solutions regarding problems in image recognition, speech recognition, object recognition, and natural language with its increasing number of libraries that are available in Python. The aim of deep learning is to develop deep neural networks by increasing and improving the number of training layers for each network, so that a machine learns more about the data until it's as accurate as possible. Developers can avail the techniques provided by deep learning to accomplish complex machine learning tasks, and train AI networks to develop deep levels of perceptual recognition. Deep learning is the next step to machine learning with a more advanced implementation. Currently, it's not established as an industry standard, but is heading in that direction and brings a strong promise of being a game changer when dealing with raw unstructured data.

Virtual reality and robotics will become widely adopted in education in the next two to three years, while wearable devices are expected to become mainstream in the education space over the next four to five years, according to a recent report published by the New Media Consortium and the Consortium for School Networking. The "NMC/CoSN Horizon Report: 2016 K–12 Edition" examined emerging technologies for their potential impact on and use in teaching, learning and creative inquiry in schools. The report, released at the end of 2016, looked at tech trends in the short term (one year or less), mid-term (two to three years) and long term (four to five years. The VR market in general is certainly heating up. Goldman Sachs recently estimated that virtual and augmented reality entertainment revenue will reach $3.2 billion by 2025, while the education sector will attract 15 million users, the report said.

Time series forecasting is an important area of machine learning that is often neglected. It is important because there are so many prediction problems that involve a time component. These problems are neglected because it is this time component that makes time series problems more difficult to handle. In this post, you will discover time series forecasting. What is Time Series Forecasting?

Which authors of this paper are endorsers? Disable MathJax (What is MathJax?)

SANTA MONICA, CA – Consumer Watchdog today called on Uber to release information about testing its robot cars in Arizona after pulling them out of San Francisco and to answer 10 questions about its vision for self-driving vehicles. In a letter to Uber CEO Travis Kalanick Consumer Watchdog's Privacy Project Director John M. Simpson wrote: "Consumer Watchdog believes you opted to pick up your toys and move because you wanted to keep important information about your robot car testing secret. We would welcome your proving our conclusion to be incorrect, by making public important information about your robot car activities. Using public highways as your laboratory carries the obligation of telling the public what you are doing." Consumer Watchdog noted that had Uber obtained a testing permit in California, the company would have been required to report any crashes of its robot cars to the Department of Motor Vehicles and to file annual disengagement reports, explaining when the robot car turned control over to the test driver and when the test driver felt it necessary to intervene.

The contentious presidential campaign was filled with accusations of elitism and bias by the media -- from the news to entertainment. Many supporters of Donald J. Trump saw his victory as a repudiation of the so-called liberal elite. So as 2017 begins, we ask: Is Hollywood representing all Americans? Are Hollywood values out of sync with American values? It's the start of a conversation we'll have all year with Hollywood's creators, consumers and observers. Most of all, we want to hear from you . Is Hollywood out of touch with your America? Here's what our critics and writers have to say: KENNETH TURAN on potent Hollywood visions that helped elect Trump TV's affluent bubble: MARY McNAMARA on Hollywood's reluctance to deal with class issues Fear of the powerful woman: JUSTIN CHANG on working women and men still behaving badly Realistic or cliche?: JEFFREY FLEISHMAN on film's working class men and women Building distrust: LORRAINE ALI on destructive TV portrayals of Muslims and how TV ...

Machine Learning can sound very complicated, but anyone with a will to learn can successfully apply it, if they approach it from first principles. This course, Classification Using Tree Based Models, covers a specific class of Machine Learning problems - classification problems and how to solve these problems using Tree based models. First, you'll learn about building and visualizing decision trees as well as recognizing the serious problem of overfitting and its causes. Next, you'll learn about using ensemble learning to overcome overfitting. Finally, you'll explore 2 specific ensemble learning techniques - Random Forests and Gradient boosted trees By the end of this course, you'll be able to recognize opportunities where you can use Tree based models to solve classification problems and measure how well your solution is doing.

Audi's plans to build AI-powered autonomous vehicles may have taken center stage during NVIDIA's CES press conference, but it's not the only automaker working with the company. NVIDIA announced its building smart vehicles with the folks at Mercedes-Benz, too. "Mercedes-Benz and NVIDIA share a common vision of the AI car," NVIDIA CEO Jen-Hsun Huang said. "At this point, it is clear AI will revolutionize the future of automobiles." The two firms have been working together for about three years now, and their product is almost ready for market.

WASHINGTON – The part of the human brain involved in face recognition keeps developing into adulthood, a pair of new studies found, surprising scientists who thought brain tissue growth stopped in early childhood. Researchers led by Kalanit Grill-Spector, a psychology professor at Stanford University, examined the brains of children and adults using a new type of imaging technique, focusing on an area of the cerebral cortex that plays a key role in face recognition. In a study published in Cerebral Cortex, the researchers showed that regions of the brain that recognize faces have a unique cellular makeup. In a separate study published in Science, they explained how they found microscopic structures within that region that change as children grow into adulthood. The growth in tissue mirrored changes in a person's ability to distinguish faces, which would explain why adults are better than children in telling faces apart.

Mercedes-Benz plans to introduce a production car powered by artificial intelligence in the next year as part of a collaboration with chip-maker Nvidia. Plans for the car were disclosed during a talk Friday between Sajjad Khan, Mercedes-Benz' vice president of digital vehicle and mobility, and Nvidia CEO Jen-Hsun Huang, at CES here. "I am very proud of saying that within 12 months we are rolling out a product with Nvidia," Khan said on Friday. Very few details of the car are known, including whether it will be a completely new vehicle or an existing Mercedes model. It is a product of a three-year collaboration, according to Huang.