R has been the gold standard in applied machine learning for a long time. Surveys show that it is the most popular platform used by professional data scientists. It is also preferred by the best data scientists in the world on the competitive machine learning site Kaggle.com. In this mega Ebook written in the friendly Machine Learning Mastery style that you're used to, learn how to get started, practice and apply machine learning using the R platform. As a developer you know how to pick up a new programming language quickly.

When Moocs burst onto the scene five years ago, many predicted business schools' demise. Wharton professors Christian Terwiesch and Karl Ulrich wrote Moocs are a "Trojan Horse" with the potential to "destroy" the full-time MBA. But rather than killing the campus, they have become an example of the whizzy digital innovations being embraced by even the oldest Ivy League institutions. "You can expect us to take engaged learning to another level where we implement technology. We're already moving in that direction," says Alison Davis-Blake, dean of the University Of Michigan's Ross School of Business. "Online education is one part of it," says Soumitra Dutta, dean of Cornell University's Johnson School of Management.

AI is getting bigger and smarter in Seattle. The Allen Institute for Artificial Intelligence, a sister company to Paul Allen's Institute for Brain Science, plans to hire 25 people in the next year as it prepares to take its Aristo technology to the eighth grade, moving on from teaching it fourth-grade science.

Smart robots seem to be everywhere. Whether they're performing surgery, trouncing Go champions or generating dreamy artwork, computers programmed to learn on their own are growing more intelligent by the day. Southwestern Law School professor Ryan Abbott believes that computers are even generating patentable subject matter. We just don't know about it, he says, because disclosing it on an application might render the invention unpatentable. "Now that very large companies like IBM, Pfizer and Google are investing heavily in creative computing, it's going to play a much greater role in innovation in the future," he says.

Today, more and more products and engineering teams rely on machine learning (referred to as ML through out this blog post). The abundance of open source tools and libraries also makes it much easier to learn, develop, and build ML models even for people with little prior knowledge or experience. ML is a powerful tool for many problems, but it comes with costs -- it can introduce complexity to systems which builds up over time and evolves into large technical debt. A recent publication by Google argues that it is remarkably easy to incur massive ongoing maintenance costs at the system level when applying ML (see Reference 1). At Quora, we've been using ML to tackle many interesting problems such as ranking, search, recommendation, and spam detection (see Reference 2, 3, and 4).

While traveling in Western Samoa many years ago, I met a young Harvard University graduate student researching ants. He invited me on a hike into the jungles to assist with his search for the tiny insect. He told me his goal was to discover a new species of ant, in hopes it might be named after him one day. Whenever I look up at the stars at night pondering the cosmos, I think of my ant collector friend, kneeling in the jungle with a magnifying glass, scouring the earth. I think of him, because I believe in aliens--and I've often wondered if aliens are doing the same to us.

"I had a half-cup of oatmeal, with two-tablesoons of maple syrup and a cup of coffee. Oh, I put a handful of blueberries in the oatmeal, and there was milk in the coffee. Ask someone what they had for breakfast, and this is the kind of description you might get. And that's one of the reasons keeping track of food intake is such a problem for tech that's meant to help a person lose weight or stick to a diet for other reasons. Logging food for nutrition and calories is important to sticking to a diet, according to Susan Roberts, director of the Boston-based Energy Metabolism Lab at Tufts University. "It makes people more self-aware about the junk they are eating and how little they actually enjoy it, and the shock of huge portions, et cetera.

As the tech world pivots on game-changing applications, data scientists rise to the occasion. Such is the case with Holden Karau, principal software engineer of Big Data at IBM and coauthor of Learning Spark. When asked about the current renovations within Spark, Karau said she sees this time as an "opportunity to get rid of dead weight" by streamlining certain processes. For example, she cited getting functional and relative queries to talk to each other within Spark. Two area of expansion include sequencing and machine learning.

Introduction to Bots A BOT is the most basic example of a weak AI that can do automated tasks on your behalf. Chat bots were one of the first automated programs to be called as'bots'. Web crawlers used by Search Engines like Google are a perfect example of sophisticated and advanced BOT.

The working relationship between people and technology is fundamentally shifting. Employees used to learn the language of business applications to use them. A world where Shift F9 created a new line item entry in their expenses. Since then, advances in user experience design have masked the language of technology with buttons and guided navigation. The user training toll has decreased but it has by no means gone away.