Plotting

Machine Learning


MIT Engineers Use Artificial Intelligence To Capture the Complexity of Breaking Waves

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Using machine learning along with data from wave tank experiments, MIT engineers have found a way to model how waves break. "With this, you could simulate waves to help design structures better, more efficiently, and without huge safety factors," says Themis Sapsis. The new model's predictions should help researchers improve ocean climate simulations and hone the design of offshore structures. Waves break once they swell to a critical height, before cresting and crashing into a shower of droplets and bubbles. These waves can be as big as a surfer's point break and as small as a gentle ripple rolling to shore.


What are the latest applications of Machine Learning?

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In this technologically advanced era, the demand for machine learning experts is growing rapidly as industrialists have already started using this technology for different purposes. As there is a skill shortage in this field, several job opportunities exist. It is a complex technical process that teaches computers to learn from data without being explicitly programmed. This technology also teaches computers to analyze data and get the work done without any human involvement. Though the technology is not new, people are adopting this technology nowadays. Let's know about modern-day applications of machine learning.


La veille de la cybersécurité

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We have developed a new embodied AI platform, called MyoSuite, that applies machine learning (ML) to biomechanical control problems by unifying motor and neural intelligence.


Senior Algorithm Research Engineer

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The Sensors Division focuses on advanced sensor system technology, from airborne and surface-based radar and electronic warfare to underwater acoustics, EO/IR and hyperspectral imaging. This position is with the Electronic Warfare and Novel Capabilities Group in the STR Sensors Division. We focus on technology development for advanced sensor systems, in the areas of airborne/surface-based radar, electronic warfare, data communications, and hyperspectral imaging. We develop algorithmic and hardware components, conduct experiment campaigns, and prototype systems. Design, build, and test roles within the Group include RF analog/digital hardware, advanced electronic warfare algorithms and techniques, signal processing and machine learning algorithms, cognitive electronic warfare applications, tracking/fusion, and real-time embedded processor implementation.


The value of a data science degree, as told by Microsoft's chief data scientist

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This program uses artificial intelligence and data science to help develop … A lot of the machine learning algorithms that we use today were …


Multifamily Only Beginning to Tap the Property Optimization Potential of AI

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That says that anything you can do as a human being we can augment the intelligence positions through machine learning and machine processes."


ISA FAST 5

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Discover how John Deere's New Autonomous 8R Tractor uses machine learning and artificial intelligence to help farmers make key decisions and …


Deep Learning Toolbox Documentation

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Deep Learning Toolbox provides a framework for designing and implementing deep neural networks with algorithms, pretrained models, and apps. You can use convolutional neural networks (ConvNets, CNNs) and long short-term memory (LSTM) networks to perform classification and regression on image, time-series, and text data. You can build network architectures such as generative adversarial networks (GANs) and Siamese networks using automatic differentiation, custom training loops, and shared weights. With the Deep Network Designer app, you can design, analyze, and train networks graphically. The Experiment Manager app helps you manage multiple deep learning experiments, keep track of training parameters, analyze results, and compare code from different experiments.


Free Workshop on AI Quality, Back By Popular Demand - KDnuggets

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Are you a data scientist or machine learning engineer interested in learning more about how to analyze and improve the performance and trustworthiness of your machine learning models? Then this live online course is for you! AI Quality: Driving ML Performance and Trustworthiness is a free course taught live by five experts from leading universities, including a professor from Carnegie Mellon University and Stanford University. This offer is exclusively for corporate and government practitioners. All students completing the course receive a certificate, limited edition shirt, and access to the Slack community.


Using AI in the Financial Services Industry

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In financial services, it is important to gain any competitive advantage. Your competition has access to most of the same data as you, since historical data is available to everyone in your industry. Your advantage comes with the ability to mine that data better, faster, and more accurately than your competitors. With a rapidly fluctuating market, the ability to process data faster gives you the opportunity to respond faster than ever. This is where AI-first intelligence can help you.