Artificial intelligence could be heading to Australian classrooms -- and in schools overseas, it's already there. In Bahia, Brazil, 15-year-old students David and Roama from Colegio Perfil often start their school day at home, or on the bus. They pick up their phones, log into the education app Geekie Lab, and begin their classes from wherever they are. "You can access it everywhere, as long as you have your phone with you," David said. Students from Colegio Perfil in Bahia use phones or computers to access the Geekie app.

With the growth in the UAV industry, Mid Michigan Community College (MMCC) came with a plan to offer a 6-week course in drone training that teaches the basics of owning and using a drone. Topics such as how to fly a drone under the regulations prescribed by the FAA, and the opportunities for drone use in a commercial setting will be included in the class. "If you're a hobbyist and use the drones for recreation, you still have to have your drone registered by the FAA," said Robert Guliani, a photography professor at the MMCC. "Beyond just personal interest, there are a lot of individual types of businesses that can use this technology," said Scott Govitz, Associate VP of Workforce and Economic Development. "We wanted to kick off with this training for the general population, next, we'll look at offering some of these training options to the public," added Govitz.

We've told you about it, and now it's happening. The General Data Protection Regulation (GDPR) recently got approved. Are you and your organization ready to explain your models? Jo-Fai Chow from H2O will lead us in a journey through the construction and interpretation of Machine Learning models, in an hand-on experience open to everybody (previous knowledge of ML is not required). We will discover the use of two R packages, h2o & LIME, for automatic and interpretable machine learning.

An artificial agent for financial risk and returns' prediction is built with a modular cognitive system comprised of interconnected recurrent neural networks, such that the agent learns to predict the financial returns, and learns to predict the squared deviation around these predicted returns. These two expectations are used to build a volatility-sensitive interval prediction for financial returns, which is evaluated on three major financial indices and shown to be able to predict financial returns with higher than 80% success rate in interval prediction in both training and testing, raising into question the Efficient Market Hypothesis. The agent is introduced as an example of a class of artificial intelligent systems that are equipped with a Modular Networked Learning cognitive system, defined as an integrated networked system of machine learning modules, where each module constitutes a functional unit that is trained for a given specific task that solves a subproblem of a complex main problem expressed as a network of linked subproblems. In the case of neural networks, these systems function as a form of an "artificial brain", where each module is like a specialized brain region comprised of a neural network with a specific architecture.

Education is moving away from traditional rows of students looking at the same textbook while a teacher lectures from the front of the room. Today's classrooms are not simply evolving to use more technology and digital resources; they are also investing in machine learning. Machine learning is defined as "a field of computer science that uses statistical techniques to give computer systems the ability to "learn" (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed." For example, in education, we see machine learning in learning analytics and artificial intelligence. Machine learning is essentially mining data.

In the past year there's been a bit of a careers and job scare when it comes to artificial intelligence, automation, and related technologies. Big consulting firms have conducted studies about the future of jobs and whether they will be lost to artificial intelligence. The consensus is that jobs will be lost, while some jobs will be created. "The development of automation enabled by technologies including robotics and artificial intelligence brings the promise of higher productivity (and with productivity, economic growth), increased efficiencies, safety, and convenience," said McKinsey in a study released last year. "But these technologies also raise difficult questions about the broader impact of automation on jobs, skills, wages, and the nature of work itself."

Many data mining tasks cannot be completely addressed by automated processes, such as sentiment analysis and image classification. Crowdsourcing is an effective way to harness the human cognitive ability to process these machine-hard tasks. Thanks to public crowdsourcing platforms, e.g., Amazon Mechanical Turk and CrowdFlower, we can easily involve hundreds of thousands of ordinary workers (i.e., the crowd) to address these machine-hard tasks. In this tutorial, we will survey and synthesize a wide spectrum of existing studies on crowd-powered data mining. We first give an overview of crowdsourcing, and then summarize the fundamental techniques, including quality control, cost control, and latency control, which must be considered in crowdsourced data mining. Next we review crowd-powered data mining operations, including classification, clustering, pattern mining, outlier detection, knowledge base construction and enrichment. Finally, we provide the emerging challenges in crowdsourced data mining.

Breakthroughs in machine learning (ML) and artificial intelligence (AI) are making headlines daily. These breakthroughs are now available -- and increasingly important -- to every business, helping turn a vast, complex data landscape into useful business insights. The new CI&T and Google whitepaper: "CIO's Guide to Data Analytics & Machine Learning" is designed to help business decision makers understand and implement systems to get actionable, predictive insights from their data. Your message has been sent. There was an error emailing this page.

Get your team access to Udemy's top 2,500 courses anytime, anywhere. This course is a workshop on logistic regression using R.

Machine Learning is enabling a transformation in the software industry without precedents. New Machine Learning powered predictive applications are performing jobs that were previously considered exclusive to highly skilled humans. We are already witnessing a new wave of innovation that is changing the face of all sectors of the economy. BigML is bringing the fourth edition of our Summer School in Machine Learning to Valencia. We will hold a two-day crash course ideal for business leaders, industry practitioners, advanced undergraduates, as well as graduate students, seeking a quick, practical, and hands-on introduction to Machine Learning to solve real-world problems.