We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

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 (AI) has become a buzzword in today’s tech-driven world, promising new possibilities and reshaping industries. Despite its prevalence, ...

Ben Khalesi covers the intersection of artificial intelligence and everyday tech at Android Police. With a background in AI and data science, he enjoys making technical topics approachable for those ...

When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...

In this architecture, the training process adopts a joint optimization mechanism based on classical cross-entropy loss. WiMi treats the measurement probability distribution output by the quantum ...

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 ...

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...