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R language is the world's most widely used programming language for statistical analysis, predictive modeling and data science. It's popularity is claimed in many recent surveys and studies. R programming language is getting powerful day by day as number of supported packages grows. Some of big IT companies such as Microsoft and IBM have also started developing packages on R and offering enterprise version of R. What is R? R is a free language and environment for statistical computing and graphics. You can perform a variety of tasks using R language.

When scholars explore new ideas, it seems instinctive to share their thinking. Last year computer science professors Joseph Halpern and Bart Selman became co-principal investigators for a nationwide project to ensure that robots and artificial intelligences (AIs) will act in ways beneficial to humans. "We thought we should get undergrads involved in thinking about these ideas," Selman said. Thus was born a new course, CS 4732, Ethical and Social Issues in AI, about how robots and artificial intelligences may change our world, and what we ought to be doing about it. "These undergrads may be directly involved in developing the software behind these systems," Selman added, noting that many may go on to jobs with Google, Tesla and other major players.

Philip, who was underweight when he arrived, says to Adam, who is overweight: "I'm worried that you're not eating healthily. I noticed you've been skipping dinner." Adam is meant to repeat back to Philip what he heard him say the problem is. He mumbles, barely audible, and can't seem to remember what he's just been told. He's unable to focus, and the air is thick with reluctance and embarrassment.

Welcome to part four of Learning AI if You Suck at Math. (Be sure to check out the other articles in this series: 1, 2, 3, 4, 5, 6, and 7.) Maybe you've downloaded TensorFlow and you're ready to get started with some deep learning? But then you wonder: What the hell is a tensor? Perhaps you looked it up on Wikipedia and now you're more confused than ever. Maybe you found this NASA tutorial and still have no idea what it's talking about? The problem is most guides talk about tensors as if you already understand all the terms they're using to describe the math. I hated math as a kid, so if I can figure it out, you can too!

After my first post on Anomaly Detection for Time Series post, I would like to continue presenting what I did during the course at for the Data Science for IoT Course at Department of Continued Education of the University of Oxford with Ajit Jaokar. In line with what I wrote previously, this second post will be about predictive maintenance. The post will conclude the initial exploration of the topics I covered at Oxford. When researching materials to cover this course, I had a general idea of what to look for. Having worked already in industrial environments, I had a good idea of what predictive maintenance should be and how it could be used.

Due to the recent achievements of artificial neural networks across many different tasks (such as face recognition, object detection and Go), deep learning has become extremely popular. This post aims to be a starting point for those interested in learning more about it. If you already have a basic understanding of linear algebra, calculus, probability and programming: I recommend starting with Stanford's CS231n. The course notes are comprehensive and well-written. The slides for each lesson are also available, and even though the accompanying videos were removed from the official site, re-uploads are quite easy to find online.

When it launched, the Udacity Artificial Intelligence Nanodegree program became a kind of landmark in this history of AI. There was no precedent for the program's groundbreaking combination of content, platform, partners, and services. That simply did not exist before. The first term of students to enroll and start the program got to experience something genuinely new. They were risk-takers in every sense of the term.

Beginning in fall 2017, some students and educators at the University of Michigan may be getting help on writing assignments from computers. Campus Technology reports that a team of educators developed a writing-to-learn tool called M-Write, which uses automated text analysis (ATA) to identify the strengths of a writing submission. Developed by two professors, the tool was initially meant to help students grow their conceptual learning skills in large courses and to help streamline the grading process, reports a UMich article. ATA works by "using a variety of text analysis techniques, such as vocabulary matching or topic matching, which the algorithm detects." Using M-Write also lets educators identify the students who are going to need help.

Facebook's chatbots are learning the art of the deal, bartering and deceiving their way to better terms in negotiations with humans and other bots. Artificial intelligences that can negotiate effectively would make useful virtual assistants, says Mike Lewis at Facebook's research lab. Bots could be left to arrange appointments for people, sorting out calendar clashes by themselves. Or they could negotiate with several agents at once to book a holiday or make a purchase on your behalf. Most existing bots – such as Apple's Siri or those built into chat apps like Facebook Messenger – may be able to get you a taxi or order a pizza but they can't engage in complex negotiations, says Lewis. If we want bots to help us with more complex tasks they need to become dealmakers, especially if the task involves cooperation or compromise, like negotiating the purchase or sale of a property, for example.