In this tutorial you will learn how to install OpenCV 4 on your Ubuntu system. OpenCV 4 has not been officially released yet; however, a release is expected in autumn 2018. In the meantime, we can compile and install OpenCV 4 from source using the pre-release on GitHub. Once OpenCV 4 is officially released I will update this blog post as well. So, why bother installing OpenCV 4? You may want to consider installing OpenCV 4 for further optimizations, C 11 support, more compact modules, and many improvements to the Deep Neural Network (DNN) module.

Learn to use functions and apply Codes. This course will guide you through how to use Google's TensorFlow framework to create artificial neural networks for deep learning and also the basics of Machine learning! This course aims to give you an easy to understand guide to the complexities of Google's TensorFlow framework in a way that is easy to understand and its application . Data Scientists enjoy one of the top-paying jobs, with an average salary of $120,000 according to Glassdoor and Indeed. If you've got some programming or scripting experience, this course will teach you the techniques used by real data scientists and machine learning practitioners in the tech industry - and prepare you for a move into this hot career path.

Using Pose Estimation and Conditional Adversarial Networks to create and visualize new Fortnite dances. If you know about the game Fortnite, you probably also know about the craze surrounding the in-game celebrations/emotes/dances. Gamers have spent millions of dollars purchasing dance moves with in-app purchases, making something as simple and as silly as this a big revenue generator for the game developer. This got me thinking, if the developer allowed the users to create these dances in the game and charged extra for it, they can probably make more money. As for the users, it would be really cool if we could record ourselves on a webcam and create our own celebratory dance within the game.

Using Pose Estimation and Conditional Adversarial Networks to create and visualize new Fortnite dances. If you know about the game Fortnite, you probably also know about the craze surrounding the in-game celebrations/emotes/dances. Gamers have spent millions of dollars purchasing dance moves with in-app purchases, making something as simple and as silly as this a big revenue generator for the game developer. This got me thinking, if the developer allowed the users to create these dances in the game and charged extra for it, they can probably make more money. As for the users, it would be really cool if we could record ourselves on a webcam and create our own celebratory dance within the game.

What if machine learning models, much like photographs, movies, music, and manuscripts, could be watermarked nearly imperceptibly to denote ownership, stop intellectual property thieves in their tracks, and prevent attackers from compromising their integrity? Thanks to IBM's new patent-pending process, they now can be. In a phone conversation with analysts this week Marc Stoecklin, IBM's manager of Cognitive Cybersecurity Intelligence, detailed the work of several IBM researchers who've been busy trying to find new ways to embed unique identifiers, or watermarks to you and I, into neural networks. Their concept was recently presented at the ACM Asia Conference on Computer and Communications Security (ASIACCS) 2018 in Korea, and might be deployed within IBM or make its way into a client-facing product in the very near future. "For the first time, we have a [robust] way to prove that someone has stolen an [AI] model," Stoecklin said.

Since the early days of computing, there has always been this idea that artificial intelligence would one day change the world. We've seen this future depicted in countless pop culture references and by futurist thinkers for decades, yet the technology itself remained elusive. Incremental progress was mostly relegated to fringe academic circles and expendable corporate research departments. That all changed five years ago. With the advent of modern deep learning, we've seen a real glimpse of this technology in action: Computers are beginning to see, hear, and talk.

DeepMind Health, working in collaboration with Moorfields Eye Hospital, has used artificial intelligence (AI) to analyse and detect a range of eye diseases. The research, which appears in Nature Medicine, applied deep learning techniques to thousands of historical anonymised retinal scans. Following this training, the AI system was able to recommend the correct referral decision for over 50 eye diseases with 94 per cent accuracy, matching the performance of the top medical experts in the field. With nearly 300 million people around the world living with some form of sight loss, it is hoped the work could help doctors and eye professionals spot serious conditions earlier and prioritise patient treatment. "The number of eye scans we're performing is growing at a pace much faster than human experts are able to interpret them," said Dr Pearse Keane, consultant ophthalmologist at Moorfields Eye Hospital NHS Foundation Trust and National Institute for Health Research clinician scientist at the UCL Institute of Ophthalmology.

Intel, eager to expand into new markets beyond the fading PC sector, said Thursday it has purchased a three-year-old Seattle artificial intelligence startup called Vertex.AI. It's Intel's second acquisition since the abrupt exit of chief executive Brian Krzanich in June, signaling the company continues to pursue its strategic objectives even as it seeks a new CEO. Vertex said on its website that it is now part of Intel's artificial intelligence products group and will continue hiring in Seattle for that segment. "With this acquisition, Intel gained an experienced team and (intellectual property) to further enable flexible deep learning at the edge," Intel said in a statement. The companies did not report terms of Thursday's deal. In July, Intel bought a Silicon Valley company called eASIC to complement Intel's programmable chips segment.

Intel has been on an artificial intelligence (AI) buying spree lately. On the heels of its Nervana, Mobileye, and Movidius acquisitions, it today announced that it's buying Vertex.ai, Vertex.ai will join the chipmaker's Artificial Intelligence Products Group, according to a note on its website, where it'll "support a variety of hardware" and work to integrate PlaidML, its "multi-language acceleration platform" that allows developers to deploy AI models on Linux, macOS, and Windows devices, with Intel's nGraph machine learning backend. It'll continue to develop the PlaidML, which is open source, under the Apache 2.0 license. "Intel has acquired Vertex.ai, a Seattle-based startup focused on deep learning compilation tools and associated technology," Intel said in a statement.

Welcome to the Fun and Easy Machine learning Course in Python and Keras. Are you Intrigued by the field of Machine Learning? Then this course is for you! We will take you on an adventure into the amazing of field Machine Learning. Each section consists of fun and intriguing white board explanations with regards to important concepts in Machine learning as well as practical python labs which you will enhance your comprehension of this vast yet lucrative sub-field of Data Science. This is a valid question and the answer is simple.