Graph embeddings have become a key and widely used technique within the field of graph mining, proving to be successful across a broad range of domains including social, citation, transportation and biological. Graph embedding techniques aim to automatically create a low-dimensional representation of a given graph, which captures key structural elements in the resulting embedding space. However, to date, there has been little work exploring exactly which topological structures are being learned in the embeddings process. In this paper, we investigate if graph embeddings are approximating something analogous with traditional vertex level graph features. If such a relationship can be found, it could be used to provide a theoretical insight into how graph embedding approaches function. We perform this investigation by predicting known topological features, using supervised and unsupervised methods, directly from the embedding space. If a mapping between the embeddings and topological features can be found, then we argue that the structural information encapsulated by the features is represented in the embedding space. To explore this, we present extensive experimental evaluation from five state-of-the-art unsupervised graph embedding techniques, across a range of empirical graph datasets, measuring a selection of topological features. We demonstrate that several topological features are indeed being approximated by the embedding space, allowing key insight into how graph embeddings create good representations.

Unlike humans, who are capable of continual learning over their lifetimes, artificial neural networks have long been known to suffer from a phenomenon known as catastrophic forgetting, whereby new learning can lead to abrupt erasure of previously acquired knowledge. Whereas in a neural network the parameters are typically modelled as scalar values, an individual synapse in the brain comprises a complex network of interacting biochemical components that evolve at different timescales. In this paper, we show that by equipping tabular and deep reinforcement learning agents with a synaptic model that incorporates this biological complexity (Benna & Fusi, 2016), catastrophic forgetting can be mitigated at multiple timescales. In particular, we find that as well as enabling continual learning across sequential training of two simple tasks, it can also be used to overcome within-task forgetting by reducing the need for an experience replay database.

Roundtable Analytics Inc., an AI/ML-based software company focused on improving the operational and financial performance of Emergency Departments (EDs), expanded its team of data scientists with the recent appointment of Michael Hyman, Ph.D., as vice president. Michael (Mike) Hyman has had a distinguished academic career, graduating with honors from the University of North Carolina with a Bachelor of Science in mathematics and a minor in chemistry. Pursuing his passion for the application of data science, Mike went on to earn both an M. Stat and Ph.D. in statistics from the University of Florida, one of the premier statistics graduate programs in the U.S. During his studies at UF, he was named a National Science Foundation Fellow, receiving an IGERT award for interdisciplinary training, and shared an office with the future founders of Roundtable Analytics Inc. Prior to joining Roundtable, Mike spent over five years working with the U.S. Department of Agriculture, performing statistical and geospatial research and developing the statistical methodology for projects such as the U.S. Census of Agriculture. Previously, during his spare time, Mike organized and completed a charity bike ride across the United States and is delighted to now return to his hometown of Raleigh, North Carolina.

Jeff Maggioncalda was recently named CEO of Coursera. I have interviewed both founders of the company, Andrew Ng and Daphne Koller, so I was curious about Maggioncalda's perspective on the company, education technology and the massive open online courses more generally, and his own background as an entrepreneur. Regarding the last point, Maggioncalda was previously the CEO of Financial Engines Inc, a company co-founded by economist and Nobel Prize winner William Sharpe and recently sold for $3 billion. During his 18 years as CEO of Financial Engines Inc, Maggioncalda had to pivot three times from his original idea before becoming a success. Financial Engines would go on to beocme the largest independent online retirement advice platform with more than $100b under management.

It used to be that cameras never lie. We tend to privilege visual content, trust what we see, and rely on police cams, mobile recording tools and similar devices to tell us about what is really happening on the streets, in local businesses, and more. Catherine Brooks (@catfbrooks) is an Associate Professor of Information at the University of Arizona, where she is the associate director of the School of Information and founding director of the Center for Digital Society and Data Studies. She is a Public Voices Fellow with the Op Ed Project. Take, for example, a viral video that shows a white woman calling the police as black men in Oakland attempt to barbecue. Millions are laughing, and the woman's image is being used as a meme across the Internet.

One of the behaviors considered to be uniquely human is our creativity. While many animal species create visually stunning displays or constructions -- think of a spider's delicate web or the colorful, intricate structures built by bowerbirds -- they are typically created with a practical purpose in mind, such as snagging prey or seducing a mate. Humans, however, make art for its own sake, as a form of personal expression. And as computer engineers attempt to imbue artificial intelligence (AI) with humanlike capabilities and behaviors, a question arises: Can AI create art? The AMC series "Humans," which returns June 5 for its third season, is populated by Synths -- intelligent robots that resemble people, save for their unnaturally green eyes.

Above two are intro course to deep learning. This is a Youtube channel which contains courses by Prof. Andrew Ng on various topics in deep learning. This a 14 week course, taught by Jeremy Howard. It cover most of the topics in deep learning. This course is a gentle introduction to Reinforcement Learning. It walks you through most of the topics in Reinforcement Learning in high level. This course is not taught at a basic level, so you need to be familiar with basic concepts and perhaps a little more. For more stories follow AiMantra.

You probably use machine-learning systems every day without even knowing it. The technology gives us spam filters, our Facebook News Feeds, digital assistants, search engines, Netflix picks, Amazon recommendations, fraud detection systems, chatbots and more. And it's only going to become more pervasive. For forward-looking parents, it's time to get your kids on it. Software developer and dad Dale Lane has created Machine Learning for Kids, a collection of free projects that teach students how to build with this technology.

Are you looking for game design and development courses? Here is the list of best game development courses, tutorials, training and certification for the individuals interested in becoming a game developer, game designer, game artist or a game programmer. Do you want to learn how to develop games? Then these Game Development Online Courses will show you the right path to get started. Building games is an innovative and technical art form.

Artificial Intelligence or Machine Learning, as it's better known as, is something that has garnered my interest over recent years. I even used the technology to design a company logo for a side hustle project. The expanding uses for Artificial Intelligence in business is fascinating and only becomes more exciting to see what is in store as the technology continues to mature. After being in the business for 25 years I have learnt and experienced first-hand the ever-changing landscape in which marketing continues to grow. We have seen a huge change in the industry over the last ten years, with the most prevalent and revolutionary change being the utter dependence of the online sphere. I have grown my business from strength to strength in the online realm, with platforms such as Twitter being a core tool.