Prerequisites: No prerequisites, knowledge of some undergraduate level mathematics would help but is not mandatory. Working knowledge of Python would be helpful if you want to run the source code that is provided. Taught by a Stanford-educated, ex-Googler and an IIT, IIM - educated ex-Flipkart lead analyst. This team has decades of practical experience in quant trading, analytics and e-commerce. The course is shy but confident: It is authoritative, drawn from decades of practical experience -but shies away from needlessly complicating stuff.

A recent study published in the Royal Society Open Science shows that babies can retain languages spoken to them in the first few months of life even if they move elsewhere and "forget" the language. Babies will always have some sort of familiarity with the language as long as that language was heard in its early life, researchers concluded. Dr. Jiyoun Choi and colleagues at Hanyang University in Seoul conducted the research by testing Dutch-speaking adults, who were adopted from South Korea. The point of the study was to show the adopted children were at an automatic advantage since the Korean language was spoken to them in their early life, even if they thought they had forgotten it. ''This finding indicates that useful language knowledge is laid down in [the] very early months of life, which can be retained without further input of the language and revealed via re-learning,'' Choi told BBC News.

This webinar will be the final opportunity before the close of registration for potential competitors to ask any questions they have regarding prize registration. Prior to joining, please be sure to read the Competition Guidelines, available on ai.xprize.org

NEW YORK, NY--(Marketwired - Jan 12, 2017) - Cloverleaf, a retail technology company for the modern brick-and-mortar marketer and merchandiser, today announced shelfPoint, the industry's first dynamic shelf solution with built-in emotional artificial intelligence (Emotion AI) capabilities. With shelfPoint, brands and retailers can now capture customer engagement and sentiment data at the moment of purchase decision -- something previously unavailable in physical retail stores. Despite the rise of online shopping in recent years, Forrester1 predicts that 88% of purchases in 2017 will still be made in physical stores. Yet, retailers lack the in-the-moment tools necessary to captivate shoppers and gain insights that lead to sales uplift. While advancements in e-commerce analytics have upleveled marketers' understanding of consumer behaviors, brands and retailers still have little-to-no insight as to what happens in-store.

Artificial intelligence can predict better than real doctors when patients with serious heart disorders are likely to die. That's according to a paper published this week in Radiology. A team of medics and computer scientists, led by the MRC London Institute of Medical Sciences (LMS) at Imperial College London, created what is claimed to be the first computer program that uses machine learning to study heart disease. Pulmonary hypertension, a condition that increases the level of pressure exerted on the arteries that supply oxygen to the lungs, is dangerous if left untreated. It affects up to 7,000 people in the UK, and a third of patients die of heart failure within five years of diagnosis.

The pioneer in intelligent automation, ServiceNow can further increase productivity for its customers by applying machine‑learning capabilities and data models developed by DxContinuum. As more Internet of Things devices make service requests, it is increasingly important that those requests be categorized, routed and responded to. Hundreds of thousands of machine and manual work requests can now be effectively and automatically categorized and routed for each ServiceNow customer, bringing the "intelligent automation" of today's manual processes one step closer. While artificial intelligence and automation are rapidly changing the consumer world from self‑driving cars to smarter homes, the workplace still relies on manual processes. Every day employees deal with IT incidents, HR cases, customer requests, and security alerts with back‑and‑forth emails, calls and spreadsheets.

Although there is a fear that the advent of artificial intelligence (AI) may result in an increasingly automated world with job replacements a possibility, an overwhelming majority of re/insurance executives see this phenomenon as an opportunity for their industry, according to an online survey of Intelligent Insurer readers. AI has already taken centre stage several times this year, firstly because of alleged job cuts at Fukoku Mutual Life Insurance, which implemented a system that calculates pay-outs to policyholders and apparently possesses the "cognitive technology that can think like a human." This was followed by peer-to-peer US insurer Lemonade going public with its claim of a'world record' for the speed of paying a claim, thanks to the use of AI. The poll, which asked whether executives see AI as an opportunity or threat to their job and business in the re/insurance industry, showed that 89 percent saw it as an opportunity and 11 percent perceived it as a potential threat. Several respondents were in agreement that the automation of routine tasks and streamlining of the underwriting process would free up opportunities, allowing more creativity within the industry, but also for more sophisticated analyses that are not possible today due to resource constraints.

When the world's smartest companies such as Microsoft, Google, Alphabet Inc., and Baidu are investing heavily in Artificial Intelligence (AI), the world is going to sit up and take notice. Chinese Internet giant Baidu spent USD1.5 billion on research and development. And as proof of China's strong focus on AI and Machine Learning, Sinovation Ventures, a venture capital firm, invested USD0.1 billion in "25 AI-related startups" in the last three years in China and the U.S. Research shows that although genuine intelligence may still be a bit far off, AI and Machine Learning technologies are still expected to reign in 2017. Try reading up on Microsoft Project Oxford, IBM Watson, Google Deep Mind, and Baidu Minwa, and you'll understand what I am trying to get at. In 2015, Gartner's Hype Cycle for Emerging Technologies introduced Machine Learning (ML), and the graph showed (Figure 1) that it would reach a plateau in 2 to 5 years.

Scientists say they have developed an artificial intelligence (AI) programme that is capable of predicting when patients with a serious heart disorder will die with an 80% accuracy rate. Researchers from the MRC London Institute of Medical Sciences (LMS) believe the software will allow doctors to better treat patients with pulmonary hypertension by determining how aggressive their treatment needs to be. Pulmonary hypertension is a rare blood vessel disorder whereby the heart's pulmonary arteries harden, making them less efficient at pumping blood to the lungs. Around 7,000 people in the UK suffer from the condition, which left untreated can cause fatal heart failure. Pulmonary hypertension is an incurable condition that gets worse with time, with a third of patients dying within five years of being diagnosed. This means that assessing how advanced the condition is in a patient is vital for selecting the right treatment.

Despite advances in forensic techniques, criminal investigations still rely on age-old tools such as eyewitness testimony, which can be biased and unreliable. But what if we could take advantage of other human abilities, such as sense of smell or a talent for facial recognition? Researchers are exploring that possibility and other crime-fighting techniques that rely less on human judgment and more on big data crunching such as an algorithm that predicts an offender's risk of committing another crime. These approaches need to be validated before we put them to use, but research suggests they could be a boon to the criminal justice system. Imagine witnessing a crime and being called into a police station where a detective presents you with an array of human scents.