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How to Normalize and Standardize Time Series Data in Python - Machine Learning Mastery
In this tutorial, you discovered how to normalize and standardize time series data in Python. That some machine learning algorithms perform better or even require rescaled data when modeling. How to manually calculate the parameters required for normalization and standardization. How to normalize and standardize time series data using scikit-learn in Python. That some machine learning algorithms perform better or even require rescaled data when modeling. How to manually calculate the parameters required for normalization and standardization. How to normalize and standardize time series data using scikit-learn in Python. Do you have any questions about rescaling time series data or about this post? Ask your questions in the comments and I will do my best to answer.
The Future of healthcare will be powered by AI and machine learning
Backed by sleek devices and powered by intelligent software and apps, smartphones are shaping the future of healthcare. The latest development in medical apps is the use of artificial intelligence and machine learning to analyze data and offer a diagnosis within seconds. ResApp Health, a digital healthcare solutions company based in Australia, is developing an app that can diagnose respiratory conditions with a smartphone's microphone, which acts as a stethoscope, according to MobiHealthNews. The ResAppDx app applies specially developed machine learning algorithms to the sounds, including cough sounds, which automatically identify potential respiratory conditions, including pneumonia, asthma, bronchiolitis and chronic obstructive pulmonary disease (COPD). Another company utilizing artificial intelligence advances is Beyond Verbal, which has launched a research platform that's attempting to identify biomarkers in users' voices to detect a range of health issues, including heart problems, ALS and even Parkinson's disease.
Cochlear to extract big data from hearing implants
From spray-on skin for burns victims, the electronic pacemaker, the Gardasil and Cervarix cancer vaccines, or finding the medical application of penicillin, Australia has a reputation of birthing a number of medical innovations that have changed the global healthcare industry. In 1967, Sydney-based Dr Graeme Clark began researching the possibilities of an electronic implantable hearing device, and by 1978, the first ever Cochlear implant was performed. Cochlear then celebrated its 10,000 recipient in 1994 and listed on the Australian Securities Exchange (ASX) a year later. Since then, Cochlear has performed thousands of operations and switched on the sound for those previously living in silence. It has also built an impressive global presence, but with that comes dealing with the way different countries and jurisdictions want information stored.
One Big Question: How do we manage the downside risks of AI?
If Hollywood is to be believed, the development of super-intelligent AI will spell the end of civilization as we know it and spark an unwinnable war between man and machine. It doesn't make for nearly as exciting entertainment, but artificial intelligence also offers tremendous upside, from the potential to deliver customized education to everyone, to improving disease diagnosis and treatment and eradicating poverty. Although AI researchers are focused these beneficial outcomes, the dystopian vision portrayed in so much science fiction is also a real possibility. At the recent Singularity University (SU) New Zealand Summit we talked with Neil Jacobstein, the former president and current chair of the Artificial Intelligence and Robotics Track at SU, about how the outcomes feared by so many can be avoided.
The biggest threat to artificial intelligence: Human stupidity ZDNet
Don't worry about the robots, worry about the humans. There's a huge difference between the modest aims of the artificial intelligence (AI) and machine learning being used today, and the grand ideas of creating an artificial general intelligence that could match -- and then rapidly exceed - the capabilities of a human mind As they develop, AI and machine learning will be able to take on even more complicated tasks, but it could still be half a century or more before AI capable of human-level intelligence is built. And, then, even longer before the sort of super-intelligence emerges that excites some, terrifies others and has provided plot lines for science fiction for decades. One may (eventually) lead to the other, but conflating today's AI and machine learning with tomorrow's Skynet is not helpful. Indeed, that confusion has encouraged many to exaggerate the short-term potential of existing (and often somewhat mundane) AI and machine learning technologies.
Half surface water in some countries has been lost since 1980s
More of Earth's surface is covered by liquid water now than three decades ago. But some countries in Central Asia and the Middle East have lost more than half their surface water, satellite images show. There have also been losses in the US and Australia. The changes are mainly a result of activities such as irrigation and dam building, but climate change is playing a part too. Previous studies of surface water have largely relied on how much water countries estimate they have..
Passport Robot Tells Man Of Asian Descent His Eyes Are Too Closed
Richard Lee's attempt to renew his passport was blocked after he submitted the picture to an online passport photo checker run by New Zealand's department of internal affairs. The automated system told the 22-year-old engineering student the photo was invalid because his eyes were closed, even though they were clearly open, according to a copy of the notification posted on social media site Facebook. "No hard feelings on my part, I've always had very small eyes and facial recognition technology is relatively new and unsophisticated," Lee told Reuters. "It was a robot, no hard feelings. I got my passport renewed in the end."
If all goes to plan, Amazon might be the messiest tech story of 2017
If the hype is to be believed, Amazon will be targeting Australia from Sept. 2017 with extreme prejudice. "We are going to destroy the retail environment in Australia," an Amazon staff member is reported to have said, according to the Australian Financial Review. As further indication of its intentions, there were numerous reports Wednesday the company has local trademarks pending across a variety of products, including its home assistant Amazon Echo. While Australians can already shop on Amazon, spending about A$500 to A$700 million according to research published in August by Citi, international shipping rates and wait times can be a deterrent. The rumoured launch of local distribution centres could make all the difference though, and while Amazon has been coy on offering any details, it could also launch its Prime subscription that guarantees free two-day shipping as well as access to its streaming service, Prime Video.
Robots won't kill the workforce. They'll save the global economy.
The United Nations forecasts that the global population will rise from 7.3 billion to nearly 10 billion by 2050, a big number that often prompts warnings about overpopulation. Some have come from neo-Malthusians, who fear that population growth will outstrip the food supply, leaving a hungry planet. Others appear in the tirades of anti-immigrant populists, invoking the specter of a rising tide of humanity as cause to slam borders shut. Still others inspire a chorus of neo-Luddites, who fear that the "rise of the robots" is rapidly making human workers obsolete, a threat all the more alarming if the human population is exploding. They may be the one thing that can protect the global economy from the dangers that lie ahead.
Lazy coders are training artificial intelligences to be sexist
Employers: do the ladies on your payroll have any "female weaknesses" that would make them mentally or physically unfit for the job? The question comes to you courtesy of the year 1943. It was posed in a guide to hiring women, written for the flummoxed male supervisors at Transportation Magazine tasked with integrating a new female workforce during a wartime shortage of manpower. Back then, you wouldn't be surprised to see logical reasoning like "Men are to programmers as women are to homemakers". Or "Men are to surgeons what women are to nurses".