Get started with Machine Learning with 6 evening sessions where you'll learn how to use Machine Learning to solve real problems. We'll walk through several common problems and use Machine Learning techniques to solve them. This will give you a clear understanding of the concepts as well as a comprehensive overview of the available tools and libraries. We will use the popular TensorFlow and Scikit-Learn libraries. We'll also look at other major open source projects available and their specific strengths and weaknesses so you'll know exactly what to use for your next project.

The White House sees artificial intelligence as an increasingly critical technology that can fight cyberattacks, upgrade weapons of war, improve health care and even unclog traffic for the commute home. However, the Obama administration also expects that A.I. will reduce low-level jobs and create security and ethical issues. With critical pros and cons looming, the federal government wants to work with the private sector and academia to guide A.I. in a positive direction, according to a recently released report, Preparing for the Future of Artificial Intelligence. The report was prepared by the National Science and Technology Council's subcommittee on Machine Learning and Artificial Intelligence. "A.I. can be a major driver of economic growth and social progress, if industry, civil society, government, and the public work together to support development of the technology, with thoughtful attention to its potential and to managing its risks," the report states.

Apple is once again looking to Asia to turbocharge its research and development process, this time to improve its artificial intelligence efforts. In an interview with Nikkei Asian Review, CEO Tim Cook said the future of the iPhone is AI, which will be supported by its new research and development center that will open by the end of the year in Yokohama, Japan. Cook seemed to suggest that AI in the iPhone would move beyond Siri and would actually help increase your battery life through resource management. It would also recommend music more skillfully, and perform other background tasks. As is typical with Apple, Cook stayed tight-lipped on specifics but said the Yokohama team will deal with "deep engineering" and be quite different from its planned R&D effort in China.

MediaGamma has announced the launch of a new Audience Prediction product, which is set to make a major impact on the ad tech market. By applying deep learning to unique data sets, coupled with MediaGamma's unique AI Decision Support Engine, the product is set to provide players in the ecosystem with over 90% certainty about a user's interests and demographic profile. The new product will help people to navigate uncertainty to make better decisions, and a major telecoms company has already signed up. The Audience Prediction product is the latest in a broad portfolio of products created by MediaGamma (http://www.mediagamma.com/), The start-up's world-renown team of data scientists deliver bespoke real time, prediction-based data science solutions focusing on online user behaviour.

Using a novel model of neural event dynamics, we investigate how cortical structures generate event representations during continuous narratives, and how these events are stored and retrieved from long-term memory. Our data-driven approach enables identification of event boundaries and event correspondences across datasets without human-generated stimulus annotations, and reveals that different regions segment narratives at different timescales. We also provide the first direct evidence that narrative event boundaries in high-order areas (overlapping the default mode network) trigger encoding processes in the hippocampus, and that this encoding activity predicts pattern reinstatement during recall. Finally, we demonstrate that these areas represent abstract, multimodal situation models, and show anticipatory event reinstatement as subjects listen to a familiar narrative. Our results provide strong evidence that brain activity is naturally structured into semantically meaningful events, which are stored in and retrieved from long-term memory.

More recently, research has suggested that quantum effects could offer similar advantages for the emerging field of quantum machine learning (a subfield of artificial intelligence), leading to more intelligent machines that learn quickly and efficiently by interacting with their environments. In a new study published in Physical Review Letters, Vedran Dunjko and coauthors have added to this research, showing that quantum effects can likely offer significant benefits to machine learning. "The progress in machine learning critically relies on processing power," Dunjko, a physicist at the University of Innsbruck in Austria, told Phys.org. "Moreover, the type of underlying information processing that many aspects of machine learning rely upon is particularly amenable to quantum enhancements. As quantum technologies emerge, quantum machine learning will play an instrumental role in our society--including deepening our understanding of climate change, assisting in the development of new medicine and therapies, and also in settings relying on learning through interaction, which is vital in automated cars and smart factories."

This is a follow up to an article Per wrote last year, Machine Learning in a Week, on how he kickstarted his way into machine learning (ml) by devoting five days to the subject. Follow him on Medium and check out his archive. My interest in ml stems back to 2014 when I started reading articles about it on Hacker News. I simply found the idea of teaching machines stuff by looking at data appealing. At the time I wasn't even a professional developer, but a hobby coder who'd done a couple of small projects.

That's just one takeaway from a new 48-page report White House AI report it released to policy makers this week, according to Jim Hendler, AI expert, researcher and coauthor of the new book, Social Machines: The Coming Collision of Artificial Intelligence, Social Networking and Humanity. Addressing such concerns, the report says that fears about super-intelligent and evil computers, shouldn't have much impact on current US policy toward AI. "And it gets that part right … we all need to cut past the hype and look at what's really on in AI," he said, "so we can pay attention to the real risks and opposed to the science fiction risks," he said. The things to worry about aren't the frightening HAL 9000 or Skynet scenarios, Hendler says, "but the very real economic, societal ethical and safety concerns AI poses for the foreseeable future." The report does a fair job of addressing such issues overall, he says, "and it is good as far as it goes," Hendler says.

Ryan Lochte's robbery tales weren't the only lies he concocted in Rio. As the "Dancing with the Stars" contestant revealed to New York magazine, he was contractually obligated to say he was single during the Olympics in August -- though Lochte didn't spill which company made that stipulation. The 32-year-old swimmer boasted about using dating apps during the Games to help the myth he was unattached. The bizarre admission comes days after Lochte proposed to his Playboy model girlfriend, Kayla Rae Reid, after 10 months of dating. Lochte, who was dropped by several prestigious sponsors after admitting he lied about being held up at gunpoint during a night of drunken debauchery, has kept quiet about how he first met Reid.

WIRE)--GNS Healthcare (GNS), a leading precision medicine company that applies causal machine learning technology to massive and diverse data streams to better match drugs and other health interventions to individual patients, today announced the appointment of Leslie Hoyt as Chief Operating Officer. A veteran healthcare operations leader, Hoyt, who most recently served United Health Group (NYSE:UNH) as Senior Vice President at Optum Health, will help GNS scale its operations and strategically navigate its development during a time of tremendous growth for the company. "Leslie brings an enormous passion for improving the health of individuals and the overall quality of care," said Colin Hill, CEO and Co-founder of GNS. "Her experience will be an essential asset to GNS, as more of our existing customers, as well as new customers, turn to GNS for solutions to complex problems arising from the transition to value-based care. Health plans, providers and biopharmaceutical companies are seeking deeper and more timely knowledge regarding which patients are likely to progress with disease, and which interventions will result in better outcomes for those patients at a lower total cost of care."