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 ...

In a world where urban traffic congestion and environmental concerns are escalating, innovative solutions are crucial for creating sustainable and efficient transportation systems. A groundbreaking ...

Distributed systems comprise a network of independent computing nodes that collaborate to achieve shared objectives despite challenges such as network latency, asynchrony and process failures. At the ...

MLI is an Application Programming Interface (API) designed to address the challenges of building machine learning algorithms in a distributed setting based on data-centric computing. Its primary goal ...

Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests. Systems controlled by next-generation computing ...

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 ...

Artificial intelligence and machine learning have transformed how we process information, make decisions, and solve complex problems. Behind every ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...