Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for clean-energy reactions are screened, identified, and validated across ...

This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...

Java is not the first language most programmers think of when they start projects involving artificial intelligence (AI) and machine learning (ML). Many turn first to Python because of the large ...

Cambridge, MA – If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine-learning model might think it is a new data point. In ...

Agnik International, a leading data science company with market-leading analytic products, today announced that they are developing a new distributed machine learning architecture based on decades of ...

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Here is a great learning resource for anyone wishing to dive into the field of machine learning – a complete class “Machine Learning” from Spring 2011 at Carnegie Mellon University. The course is ...