From the time of our very first deep learning course at the USF Data Institute (which was recorded and formed the basis of our MOOC), we have allowed selected students that could not participate in person to attend via video and text chat through our International Fellowship. We want to get deep learning into the hands of as many people as possible, from as many diverse backgrounds as possible. People with different backgrounds have different problems they're interested in solving. We have seen and experienced some of the obstacles facing outsiders: inequality, discrimination, and lack of access. We've also observed that the field of artificial intelligence is missing out because of its lack of diversity.

About this course: Regression Analysis is perhaps the single most important Business Statistics tool used in the industry. Regression is the engine behind a multitude of data analytics applications used for many forms of forecasting and prediction. This is the fourth course in the specialization, "Business Statistics and Analysis". The course introduces you to the very important tool known as Linear Regression. You will learn to apply various procedures such as dummy variable regressions, transforming variables, and interaction effects.

This week Microsoft and Alibaba stoked new fears that robots will soon take our jobs. The two companies independently revealed that their artificial intelligence systems beat humans at a test of reading comprehension. The test, known as the Stanford Question Answering Dataset (SQuAD), was designed to train AI to answer questions about a set of Wikipedia articles. Like the image-recognition software already deployed in commercial photo apps, these systems lend the impression that machines have become increasingly capable of replicating human cognition: identifying images or sounds, and now speed reading text passages and spewing back answers with human-level accuracy. Machine smarts, though, are not always what they seem.

This week, as leaders gather in Davos, Switzerland, to discuss how to "create a shared future in a fractured world," many of the conversations will center on the role of humans and robots in a future of automation or augmentation. The teaser for a breakfast conversation that Microsoft is hosting on the promise and pitfalls of artificial intelligence captures the challenges and the opportunity well: "AI offers profound potential benefits and the opportunity to help tackle some of the world's most pressing issues including accelerating economic growth, tackling the urgent issues of environmental sustainability, and transforming healthcare," it reads. "But the accelerating pace of technology-driven change is also creating disruption and anxiety. It risks contributing to a sense of a fractured world, between a small group of people who benefit and a broader group of people who fear that they are being left behind. We need to come together to chart a path forward that ensures AI contributes to building a positive shared future for every community."

If you want to learn how to perform the most useful statistical analyses in the R program, you have come to the right place. Now you don't have to scour the web endlessly in order to find how to do a Pearson or Spearman correlation, an independent t test or a factorial ANOVA, how to perform a sequential regression analysis or how to compute the Cronbach's alpha. Everything is here, in this course, explained visually, step by step. So, what will you learn in this course? First of all, you will learn how to perform association tests in R, both parametric and non-parametric: the Pearson correlation, the Spearman and Kendall correlation, the partial correlation and the chi-square test for independence.

The field of construction is well placed to benefit from the advent of machine learning and artificial intelligence. As part of the BIM 360 Project IQ Team at Autodesk, I've had the privilege of being a part of Autodesk's foray into machine learning for construction. This talk will focus on summarizing the developments in this space, and we'll cover some ways in which one can prepare to maximize value from this technology. The class has 2 sections. The first part provides a broad survey of some of the applications of AI and machine learning in construction, and the potential impact.

The Applied AI Conference is a must-attend event for people who are working, researching, building, and investing in Applied Artificial Intelligence technologies and products.

Beginning in February, Microsoft plans to offer a new feature for young students: Immersive Reader dictation, a new feature within Office 365 apps for Windows and the Mac. As a parent of two elementary school students, though, I'm concerned this feature will be an unwelcome crutch. Microsoft is pushing dictation onto Word for Mac, iPhone, Outlook Desktop, OneNote iPad, and OneNote Mac. Even though I write about technology for a living, I'm sort of feeling my way through applying it toward parenting. Is a smart speaker an annoyance or a learning aid?

What we are looking at is a recommendation engine problem. Given the personal data you want to make the diet recommendation that are best suited for the person based on the data inserted. For creating this recommendation engine, you'll need data for personal details and appropriate recommendations. Based on this training data, you'll create the recommendation engine which will map the personal information to appropriate diet recommendations.

Microsoft and Alibaba have independently developed AI models that scored better than humans in a Stanford University reading comprehension test. This AI milestone was reached using the Stanford Question Answering Dataset (SQuAD), which consists of over 10,000 question-and-answer pairs that apply to more than 500 Wikipedia articles. Alibaba's model achieved a score of 82.44, while the submission from Microsoft Research Asia bested that with a mark of 82.65. The human score for the SQuAD test is 82.304. Although that's a slim margin to claim superior performance, it represents the first time any natural language processing (NLP) software has been able to eclipse humans on this particular benchmark.