Your.MD is truly revolutionary and can make a seismic impact on the global healthcare system by providing accessible, trustworthy and instant healthcare to everyone with a mobile phone, said Matteo Berlucchi, Your.MD's chief executive in the announcement. Our OneStop Health is an integral part of our vision; if you can't get to your doctor or need to get a blood test, a prescription or make an appointment to see the best local specialist, Your.MD can facilitate it – safely and responsibly by connecting you to the best service providers and products who can help you get what you need.

In this article we conclude our four part series on basic model testing. When fitting and selecting models in a data science project, how do you know that your final model is good? And how sure are you that it's better than the models that you rejected? In this concluding Part 4 of our four part mini-series "How do you know if your model is going to work?" we demonstrate cross-validation techniques. Cross validation techniques attempt to improve statistical efficiency by repeatedly splitting data into train and test and re-performing model fit and model evaluation.

Guest blog post by Christopher Dole and other contributors, originally posted here. Deep Learning is one of the most revolutionary and disruptive technologies ever developed in Data Science. Essentially, this is a class of algorithms inspired by how the human brain works, and it has the ability to automate and replace most of the world's jobs. This is what enables self-driving cars to function and what allows Spotify to create very customized playlists and recommendations. This is how YouTube is able to identify faces and animals in videos and how Siri can understand and process free speech in milliseconds.

If you think of each day as a conference crammed into a day, you get a good flavor of things. Here are some of the interesting things I saw.

The last few years have seen considerable advances in artificial intelligence (AI) using technology inspired by animal brains. Neural networks and deep reinforcement learning allowed Google Deep Mind's AlphaGo AI to beat champion Go player Lee Se-dol. The same methods are being used to teach AI to explore in Minecraft and win deathmatches in Doom. Neural networks can even influence the art world. Google's Deep Mind famously produces surreal art that took the internet by storm.

Deep Learning is one of the most revolutionary and disruptive technologies ever developed in Data Science. Essentially, this is a class of algorithms inspired by how the human brain works, and it has the ability to automate and replace most of the world's jobs. This is what enables self-driving cars to function and what allows Spotify to create very customized playlists and recommendations. This is how YouTube is able to identify faces and animals in videos and how Siri can understand and process free speech in milliseconds. Deep Learning has also led to several recent advancements in healthcare.

Last week an artificial intelligence won the first Go game against the human. Yesterday, the same software lost because it rated as highly improbable a move by the human player. While machine learning progresses exponentially, it keeps on having trouble coping with rare events. As long as artificial intelligences are used to play games, this issue does not really matter. Ignoring the event is arguably a good strategy in such a context, as it ensures that the majority of games will be won over a large number of games.

Today Silicon Valley chip maker Movidius released the Fathom Neural Compute Stick. It looks like a measly thumb drive, but inside it packs a high-end visual processing unit that can do a bunch of advanced image recognition. That chip, which is called the Myriad 2, is the same one powering the computer vision and autonomous features in DJI's latest drone. The Fathom is basically a plug-and-play version of the Myriad 2, and Movidius hopes engineers will use it to build deep learning features like like pixel-by-pixel imagine labeling and advanced video analytics into their existing products. "It lets you implement machine learning in an ad hoc manner," Cormac Brick, head of machine learning at Movidius, tells The Verge.

Tesla CEO Elon Musk introduces the Model X. I think we should be very careful about artificial intelligence. If I had to guess at what our biggest existential threat is, it's probably that. So we need to be very careful with artificial intelligence...With artificial intelligence, we're summoning the demon. You know those stories where there's the guy with the pentagram, and the holy water, and he's like -- Yeah, he's sure he can control the demon?

High-tech entrepreneur Elon Musk has launched an open-source training "gym" for artificial-intelligence programmers. It's an interesting move for a man who in 2014 said artificial intelligence, or A.I., will pose a threat to the human race. "I think we should be very careful about artificial intelligence," Musk said about a year and a half ago during an MIT symposium. "If I were to guess at what our biggest existential threat is, it's probably that... with artificial intelligence, we are summoning the demon. In all those stories with the guy with the pentagram and the holy water, and he's sure he can control the demon. Today, Musk is moving to help programmers use A.I. and machine learning to build smart robots and smart devices. "We're releasing the public beta of OpenAI Gym, a toolkit for developing and comparing reinforcement learning (RL) algorithms," wrote Greg Brockman, OpenAI's CTO, and John Schulman, a scientist working with OpenAI, in a blog post . "We originally built OpenAI Gym as a tool to accelerate our own RL research.