Compared to other programming exercises, a machine learning project is a blend of code and data. You need both to achieve the result and do something useful. Over the years, many well-known datasets have been created, and many have become standards or benchmarks. In this tutorial, we are going to see how we can obtain those well-known public datasets easily. We will also learn how to make a synthetic dataset if none of the existing datasets fits our needs.

Now, AI at IU has a home. IU President Michael A. McRobbie dedicated the $35 million Luddy Center for Artificial Intelligence, a 58,000-square-foot facility that will serve as the hub for multidisciplinary research in advanced AI and machine-learning applications, during a ceremony June 23 at Luddy Hall. "As we dedicate the Luddy Center for Artificial Intelligence, it is fair to say that we are also celebrating what will be a game-changing development for Indiana University," McRobbie said. "Indiana University has been a center of research in a number of areas of AI for many years. Artificial intelligence has long been an area of strength of the Department of Computer Science and, more broadly, IU faculty in the cognitive sciences, psychological sciences and neurosciences have also long been engaged in areas of research relevant to AI. The explosion worldwide of the uses and applications of AI, building on decades of steady research progress, made this the perfect time for IU to establish a major holistic initiative in artificial intelligence."

Budding authors face a minefield when it comes to publishing their work. For a large fee, as much as $3,000, they can make their work available to anyone who wants to read it. Or they can avoid the fee and have readers pay the publisher instead. Often it is libraries that foot this bill through expensive annual subscriptions. This is not the lot of wannabe fiction writers, it's the business of academic publishing.

The technique, not unknown in AI research, uses a larger, more robust neural network to teach another network the decisions it would make in a variety of situations. It's unclear whether Apple's pledge to publish will apply only to machine-learning research, or to other areas of computer-science research, like security. A bragging point for Apple was the efficiency of its algorithms on graphics processing units, or GPUs, the hardware commonly used in servers to speed processing in deep learning. Apple has long been secretive about the research done within its Cupertino, California, labs. By slimming down the neural network, iPhones and iPads can identify faces and locations in photos, or understand changes in a user's heart rate, without needing to rely on remote servers. The technique, not unknown in AI research, uses a larger, more robust neural network to teach another network the decisions it would make in a variety of situations.

Machine-learning research has been making great progress in many directions. The four directions are (1) the improvement of classification accuracy by learning ensembles of classifiers, (2) methods for scaling up supervised learning algorithms, (3) reinforcement learning, and (4) the learning of complex stochastic models.